[1] "Search CASE_STATUS for CERTIFIED"
[1] "Group by EMPLOYER_NAME2"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 426,203"
[1] "SUM(APPLICATIONS) = 257,283"
[1] "NUMBER OF ROWS = 38,382"
[1] "MEDIAN(LOW_WAGE) = NULL"
[1] "MEAN(LOW_WAGE) = NA"
[1] ""
EMPLOYER_NAME2 WORKERS APPLICATIONS
1 GOOGLE 7158 7053
2 COGNIZANT TECHNOLOGY SOLUTIONS US 5521 5521
3 ERNST & YOUNG U.S 5113 5113
4 AMAZON.COM 5467 4783
5 MICROSOFT 4564 4414
6 DELOITTE CONSULTING 9071 4273
7 APPLE 6888 2908
8 FACEBOOK 6594 2519
9 WAL-MART ASSOCIATES 1586 1586
10 ANTHEM 1583 1496
11 WELLS FARGO 1583 1467
12 JPMORGAN CHASE 1613 1462
13 SALESFORCE.COM 1528 1316
14 AMERICAN EXPRESS 1276 1124
15 CAPITAL ONE 1176 1119
16 CISCO SYSTEMS 6274 1116
17 INTERNATIONAL BUSINESS MACHINES 1027 1027
18 FORD MOTOR 1334 923
19 GOLDMAN SACHS 914 909
20 DELOITTE & TOUCHE 2741 893
21 AT&T 986 879
22 AMAZON WEB 874 852
23 VERIZON 932 807
24 INTEL 2036 778
25 LINKEDIN 1022 755
26 PAYPAL 1027 731
27 VMWARE 814 728
28 BANK OF AMERICA 677 658
29 CITIGROUP 668 644
30 INFOSYS 861 631
31 BANK OF AMERICA N.A 675 630
32 CHARTER COMMUNICATIONS 708 612
33 EBAY 722 577
34 BLACKROCK FINANCIAL MANAGEMENT 559 559
35 IBM 514 514
36 FANNIE MAE 675 508
37 WALMART 617 486
38 CVS HEALTH 513 485
39 FEDEX 534 480
40 KPMG 700 478
41 NIKE 637 470
42 COMCAST CABLE COMMUNICATIONS 462 462
43 QUALCOMM TECHNOLOGIES 29737 458
44 UBER TECHNOLOGIES 2339 444
45 PRICEWATERHOUSECOOPERS ADVISORY 440 440
46 FIDELITY INVESTMENTS 664 439
47 PRICEWATERHOUSECOOPERS 469 438
48 MICRON 437 435
49 COMCAST 578 435
50 CUMMINS 433 431
51 MORGAN STANLEY SERVICES GROUP 429 429
52 CERNER 423 423
53 OATH HOLDINGS 743 422
54 CHARLES SCHWAB 599 398
55 ACCENTURE 401 396
56 AMGEN 406 392
57 KAISER PERMANENTE 865 387
58 ADVANCED MICRO DEVICES 397 386
59 INTUIT 713 385
60 DELOITTE TAX 1260 378
61 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
62 T-MOBILE USA 414 368
63 ORACLE AMERICA 8733 363
64 STATE STREET BANK & TRUST 409 356
65 VISA TECHNOLOGY & OPERATIONS 502 356
66 AMERICAN AIRLINES 412 354
67 CVS PHARMACY 390 349
68 DISCOVER 346 337
69 HCL AMERICA 335 335
70 PNC BANK 1456 333
71 OPTUM 352 332
72 CAPGEMINI AMERICA 326 326
73 EQUIFAX 362 313
74 JOHNSON & JOHNSON 376 310
75 TESLA 309 309
76 CREDIT SUISSE SECURITIES (USA) 320 308
77 HUMANA 412 307
78 ADP 409 305
79 MAYO CLINIC 305 305
80 JP MORGAN CHASE 316 302
81 HEWLETT PACKARD ENTERPRISE 1759 301
82 GENERAL MOTORS 305 300
83 HOME DEPOT 309 299
84 BOSTON CONSULTING GROUP 289 289
85 CIGNA 571 289
86 NVIDIA 6954 285
87 GENERAL ELECTRIC 289 280
88 UNITED AIRLINES 540 277
89 CITIBANK N.A 301 273
90 VERIZON SOURCING 436 272
91 BLOOMBERG L.P 823 272
92 VISA U.S.A 326 268
93 ADOBE 820 265
94 MCKINSEY & COMPANY INC UNITED STATES 4024 261
95 CATERPILLAR 286 261
96 TATA CONSULTANCY 264 260
97 WELLS FARGO BANK N.A 396 259
98 NORTHERN TRUST 271 258
99 EXPEDIA 665 257
100 MERCK 288 257
101 GILEAD SCIENCES 2529 255
102 SAP AMERICA 253 253
103 DFS 252 252
104 FCA US 364 243
105 METLIFE 452 243
106 BOFA SECURITIES 240 240
107 JUNIPER NETWORKS 346 240
108 SPRINT 240 240
109 SERVICENOW 4401 239
110 CENTENE 247 238
111 KROGER 354 233
112 SUNTRUST BANKS 291 233
113 ABBVIE 267 232
114 EXPRESS SCRIPTS 239 231
115 NATSOFT 223 223
116 MINDTREE 220 220
117 WAYFAIR 1427 220
118 EMC 216 216
119 HEALTH CARE SERVICE 272 215
120 BARCLAYS 214 214
121 PFIZER 435 214
122 AT & T 338 213
123 VANGUARD 257 209
124 MORGAN STANLEY 217 208
125 FORUM CAPITAL MARKETS LLC (DBA WELLS FAR 207 207
126 GAP 332 203
127 WAYMO 207 203
128 RIVIAN AUTOMOTIVE 221 202
129 T-MOBILE 266 200
130 APPLIED MATERIALS 1023 198
131 STATE FARM MUTUAL AUTOMOBILE INSURANCE 237 198
132 MEDTRONIC 240 197
133 COX AUTOMOTIVE 201 196
134 MACY'S SYSTEMS & 339 196
135 BEST BUY 200 194
136 METROPOLITAN LIFE INSURANCE 220 193
137 DISCOVER PRODUCTS 192 192
138 COMCAST CABLE COMMUNICATIONS MANAGEMENT 236 192
139 VERIZON DATA 190 190
140 U.S BANK NATIONAL ASSOCIATION 190 190
141 CHEVRON 235 189
142 FIDELITY TECHNOLOGY GROUP 188 188
143 SCHLUMBERGER 198 187
144 CARDINAL HEALTH 193 186
145 NATIONWIDE INSURANCE 185 185
146 LOWE'S COMPANIES 184 184
147 NORDSTROM 183 183
148 UNIVERSITY OF MICHIGAN 181 181
149 TRAVELERS 184 180
150 MASTERCARD INTERNATIONAL 279 177
151 CADENCE DESIGN SYSTEMS 485 177
152 VANGUARD GROUP 184 177
153 HP 907 174
154 TECH MAHINDRA (AMERICAS) 172 172
155 TOYOTA 346 172
156 BDO USA 170 170
157 MATHWORKS 170 170
158 BOEING 208 170
159 AKAMAI TECHNOLOGIES 168 168
160 SOUTHWEST AIRLINES 257 168
161 MUFG UNION BANK N.A 191 168
162 AECOM TECHNICAL 167 167
163 WESTERN DIGITAL TECHNOLOGIES 4960 165
164 MCKESSON 168 163
165 HARTFORD 168 163
166 ERICSSON 162 162
167 LIBERTY MUTUAL INSURANCE 613 162
168 MOLINA HEALTHCARE 171 162
169 UBS BUSINESS SOLUTIONS US 168 161
170 TWITTER 190 161
171 PEPSICO 165 160
172 TEXAS INSTRUMENTS 169 160
173 LYFT 167 157
174 SONY INTERACTIVE ENTERTAINMENT 223 156
175 AUTODESK 223 156
176 AIRBNB 158 156
177 FIDELITY MANAGEMENT & RESEARCH 156 156
178 NATIONWIDE MUTUAL INSURANCE 155 155
179 IQVIA 162 153
180 TARGET ENTERPRISE 153 153
181 DXC 2135 153
182 BANK OF NEW YORK MELLON 153 153
183 FARMERS INSURANCE GROUP 176 153
184 SQUARE 152 152
185 SLALOM 235 152
186 FISERV 199 152
187 ALLY FINANCIAL 244 149
188 WELLS FARGO BANK 280 148
189 ZILLOW 147 147
190 TOYOTA MOTOR NORTH AMERICA 227 147
191 NXP USA 146 146
192 3M 159 145
193 VERIZON COMMUNICATIONS 217 145
194 ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI 144 144
195 DELL USA L.P 149 143
196 BECTON DICKINSON 147 143
197 PACIFIC GAS & ELECTRIC 150 141
198 ALLSTATE INSURANCE 223 141
199 MEMORIAL SLOAN KETTERING CANCER CENTER 140 140
200 PALO ALTO NETWORKS 583 139
201 DROPBOX 139 139
202 THERMO FISHER SCIENTIFIC 187 138
203 UNIVERSITY OF CALIFORNIA SAN FRANCISCO 138 138
204 AMERISOURCEBERGEN 143 138
205 HOME DEPOT PRODUCT AUTHORITY 138 138
206 ABBOTT LABORATORIES 147 137
207 INDEED 137 137
208 PROKARMA 136 136
209 PNC 480 136
210 7-ELEVEN 144 134
211 KLA 134 134
212 AETNA RESOURCES 132 132
213 STATE FARM 306 132
214 ONCOR ELECTRIC DELIVERY 146 131
215 NUTANIX 601 130
216 HARVARD UNIVERSITY 130 130
217 WORKDAY 1050 130
218 TRAVELERS INDEMNITY 134 130
219 WALGREENS 135 130
220 ANALOG DEVICES 129 129
221 LELAND STANFORD JR UNIVERSITY 129 129
222 NETFLIX 127 127
223 DEERE 136 127
224 SAP LABS 126 126
225 MOTOROLA SOLUTIONS 136 126
226 COLUMBIA UNIVERSITY 126 126
227 FIS MANAGEMENT 126 126
228 ASML US LP 125 125
229 TRUSTEES OF THE UNIVERSITY OF PENNSYLVAN 124 124
230 JOHNS HOPKINS UNIVERSITY 124 124
231 FREDDIE MAC 128 123
232 EQUINIX 131 122
233 COGNIZANT WORLDWIDE 122 122
234 AETNA 124 122
235 CAPITAL GROUP COMPANIES 212 122
236 MARRIOTT INTERNATIONAL 137 121
237 WALGREEN 121 121
238 AMERIPRISE FINANCIAL 131 121
239 UNIVERSITY OF PITTSBURGH 122 120
240 MASTERCARD 325 120
241 VERIZON WIRELESS 130 120
242 CAREMARK 119 119
243 SAPIENT 119 119
244 SNAP 291 119
245 GLOBALFOUNDRIES U.S 119 119
246 REGENERON PHARMACEUTICALS 124 118
247 SOUTHERN CALIFORNIA EDISON 167 118
248 SPLUNK 170 117
249 TRUIST BANK 164 117
250 SAMSUNG ELECTRONICS AMERICA 116 116
251 APPSTEK 116 116
252 GENENTECH 117 115
253 GOVERNMENT EMPLOYEES INSURANCE COMPANY ( 113 113
254 ST JUDE CHILDREN'S RESEARCH HOSPITAL 113 113
255 CAPITAL ONE NATIONAL ASSOCIATION 113 113
256 CREDIT SUISSE SERVICES (USA) 113 113
257 INTUITIVE SURGICAL OPERATIONS 113 113
258 CISCO 237 113
259 PRUDENTIAL FINANCIAL 158 113
260 ELI LILLY 148 113
261 GENPACT 112 112
262 STATE FARM INSURANCE 113 111
263 UNITED PARCEL SERVICE 111 111
264 NETAPP 112 110
265 COX COMMUNICATIONS 110 110
266 FIDELITY BROKERAGE 110 110
267 DELTA AIR LINES 109 109
268 BLUE SHIELD OF CALIFORNIA 140 108
269 FIAT CHRYSLER AUTOMOBILES 260 108
270 GE DIGITAL HOLDINGS 108 108
271 ERNST & YOUNG 108 107
272 ECLINICALWORKS 105 105
273 CBRE 109 105
274 HORIZON BLUE CROSS BLUE SHIELD OF NEW JE 105 105
275 UT SOUTHWESTERN MEDICAL CENTER 104 104
276 DEUTSCHE BANK SECURITIES 104 104
277 STAPLES 103 103
278 INSURANCE SERVICES OFFICE 103 103
279 NOKIA OF AMERICA 103 103
280 BRISTOL-MYERS SQUIBB 103 103
281 DB USA CORE 102 102
282 CHARTER COMMUNICATIONS OPERATING 115 102
283 TJX COMPANIES 116 101
284 NEW YORK UNIVERSITY 101 101
285 BYTEDANCE 101 101
286 BLUE CROSS BLUE SHIELD OF MICHIGAN 100 100
287 NATIONAL INSTITUTES OF HEALTH HHS 100 100
288 KEYBANK NATIONAL ASSOCIATION 107 99
289 ARM 2325 99
290 CYBERSOURCE 157 99
291 ATLASSIAN 99 99
292 WASHINGTON UNIVERSITY 99 99
293 JP MORGAN CHASE BANK N.A 104 98
294 ASURION 97 97
295 DISH NETWORK 102 97
296 AMERICAN INTERNATIONAL GROUP 97 97
297 DUKE ENERGY 97 97
298 CREDIT SUISSE 107 97
299 SAMSUNG AUSTIN SEMICONDUCTOR L.L.C 96 96
300 EPAM SYSTEMS 1227 96
[1] "Search CASE_STATUS for CERTIFIED"
[1] "Search Primary Sites Only"
[1] "Group by EMPLOYER_NAME2"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 315,457"
[1] "SUM(APPLICATIONS) = 173,092"
[1] "NUMBER OF ROWS = 26,371"
[1] "MEDIAN(LOW_WAGE) = NULL"
[1] "MEAN(LOW_WAGE) = NA"
[1] ""
EMPLOYER_NAME2 WORKERS APPLICATIONS
1 GOOGLE 6496 6496
2 COGNIZANT TECHNOLOGY SOLUTIONS US 5520 5520
3 ERNST & YOUNG U.S 5113 5113
4 AMAZON.COM 5449 4769
5 MICROSOFT 4220 4133
6 DELOITTE CONSULTING 8876 4109
7 FACEBOOK 6315 2320
8 APPLE 5671 1864
9 WAL-MART ASSOCIATES 1586 1586
10 JPMORGAN CHASE 1352 1320
11 SALESFORCE.COM 1500 1294
12 INTERNATIONAL BUSINESS MACHINES 986 986
13 DELOITTE & TOUCHE 2720 890
14 AMAZON WEB 872 850
15 GOLDMAN SACHS 818 818
16 LINKEDIN 969 717
17 VMWARE 790 714
18 CISCO SYSTEMS 5793 686
19 INTEL 1816 649
20 INFOSYS 807 582
21 CAPITAL ONE 578 578
22 BANK OF AMERICA N.A 578 578
23 PAYPAL 752 578
24 BLACKROCK FINANCIAL MANAGEMENT 558 558
25 EBAY 592 476
26 IBM 461 461
27 PRICEWATERHOUSECOOPERS ADVISORY 440 440
28 QUALCOMM TECHNOLOGIES 29712 440
29 KPMG 658 436
30 UBER TECHNOLOGIES 2325 430
31 ANTHEM 426 426
32 OATH HOLDINGS 743 422
33 CERNER 413 413
34 MORGAN STANLEY SERVICES GROUP 411 411
35 MICRON 393 393
36 DELOITTE TAX 1260 378
37 ADVANCED MICRO DEVICES 388 377
38 ACCENTURE 369 369
39 ORACLE AMERICA 8731 361
40 PRICEWATERHOUSECOOPERS 355 355
41 VISA TECHNOLOGY & OPERATIONS 500 354
42 COMCAST CABLE COMMUNICATIONS 347 347
43 AMGEN 326 326
44 CAPGEMINI AMERICA 318 318
45 INTUIT 566 303
46 HCL AMERICA 290 290
47 TESLA 288 288
48 BOSTON CONSULTING GROUP 281 281
49 CHARTER COMMUNICATIONS 272 272
50 CREDIT SUISSE SECURITIES (USA) 271 271
51 BLOOMBERG L.P 820 269
52 NVIDIA 6926 267
53 VISA U.S.A 323 265
54 AMERICAN EXPRESS 314 263
55 CUMMINS 261 261
56 MCKINSEY & COMPANY INC UNITED STATES 4024 261
57 MAYO CLINIC 258 258
58 TATA CONSULTANCY 260 256
59 OPTUM 252 252
60 EXPEDIA 654 246
61 SAP AMERICA 245 245
62 ADOBE 798 243
63 GENERAL MOTORS 241 241
64 BOFA SECURITIES 240 240
65 DFS 234 234
66 FORD MOTOR 229 229
67 SERVICENOW 4385 223
68 NATSOFT 223 223
69 CITIBANK N.A 218 218
70 WAYFAIR 1425 218
71 ADP 319 217
72 HEWLETT PACKARD ENTERPRISE 1549 216
73 EMC 213 213
74 MINDTREE 205 205
75 WAYMO 202 202
76 STATE STREET BANK & TRUST 193 193
77 DISCOVER PRODUCTS 191 191
78 FIDELITY TECHNOLOGY GROUP 188 188
79 RIVIAN AUTOMOTIVE 204 187
80 BARCLAYS 184 184
81 U.S BANK NATIONAL ASSOCIATION 182 182
82 UNIVERSITY OF MICHIGAN 181 181
83 JUNIPER NETWORKS 285 179
84 T-MOBILE USA 176 176
85 CADENCE DESIGN SYSTEMS 479 171
86 BDO USA 170 170
87 AKAMAI TECHNOLOGIES 168 168
88 MASTERCARD INTERNATIONAL 269 167
89 AECOM TECHNICAL 167 167
90 MATHWORKS 167 167
91 TECH MAHINDRA (AMERICAS) 166 166
92 AMERICAN AIRLINES 158 158
93 TWITTER 187 158
94 NORDSTROM 156 156
95 TARGET ENTERPRISE 152 152
96 SQUARE 152 152
97 SLALOM 235 152
98 UBS BUSINESS SOLUTIONS US 151 151
99 FIDELITY MANAGEMENT & RESEARCH 151 151
100 FCA US 150 150
101 COX AUTOMOTIVE 149 149
102 AIRBNB 148 148
103 WESTERN DIGITAL TECHNOLOGIES 4938 147
104 VERIZON DATA 147 147
105 MACY'S SYSTEMS & 289 146
106 ZILLOW 146 146
107 ERICSSON 145 145
108 TEXAS INSTRUMENTS 145 145
109 SONY INTERACTIVE ENTERTAINMENT 144 144
110 LOWE'S COMPANIES 144 144
111 ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI 144 144
112 LYFT 143 143
113 FEDEX 143 143
114 NXP USA 141 141
115 SCHLUMBERGER 141 141
116 DELL USA L.P 139 139
117 MEMORIAL SLOAN KETTERING CANCER CENTER 138 138
118 HOME DEPOT PRODUCT AUTHORITY 138 138
119 INDEED 137 137
120 UNIVERSITY OF CALIFORNIA SAN FRANCISCO 136 136
121 AUTODESK 197 135
122 PROKARMA 134 134
123 AETNA RESOURCES 132 132
124 DROPBOX 131 131
125 LELAND STANFORD JR UNIVERSITY 129 129
126 IQVIA 128 128
127 HP 797 127
128 NETFLIX 126 126
129 FIS MANAGEMENT 126 126
130 COLUMBIA UNIVERSITY 125 125
131 TRUSTEES OF THE UNIVERSITY OF PENNSYLVAN 124 124
132 SAP LABS 124 124
133 KLA 124 124
134 JOHNS HOPKINS UNIVERSITY 123 123
135 ASML US LP 123 123
136 NUTANIX 593 122
137 COGNIZANT WORLDWIDE 122 122
138 PALO ALTO NETWORKS 565 121
139 ANALOG DEVICES 120 120
140 WELLS FARGO BANK N.A 119 119
141 NIKE 119 119
142 SNAP 291 119
143 HARVARD UNIVERSITY 119 119
144 UNIVERSITY OF PITTSBURGH 119 119
145 CAREMARK 118 118
146 SAPIENT 117 117
147 GLOBALFOUNDRIES U.S 117 117
148 APPLIED MATERIALS 940 115
149 WORKDAY 1033 115
150 CAPITAL ONE NATIONAL ASSOCIATION 113 113
151 ST JUDE CHILDREN'S RESEARCH HOSPITAL 112 112
152 GOVERNMENT EMPLOYEES INSURANCE COMPANY ( 111 111
153 CHARLES SCHWAB 111 111
154 GENPACT 111 111
155 CREDIT SUISSE SERVICES (USA) 111 111
156 TRUIST BANK 158 111
157 FIDELITY BROKERAGE 110 110
158 AT&T 109 109
159 GE DIGITAL HOLDINGS 108 108
160 GILEAD SCIENCES 2365 106
161 ECLINICALWORKS 105 105
162 EQUIFAX 104 104
163 DEUTSCHE BANK SECURITIES 104 104
164 CVS PHARMACY 103 103
165 INSURANCE SERVICES OFFICE 103 103
166 UT SOUTHWESTERN MEDICAL CENTER 103 103
167 DB USA CORE 102 102
168 NOKIA OF AMERICA 101 101
169 BYTEDANCE 101 101
170 SPLUNK 149 100
171 NATIONAL INSTITUTES OF HEALTH HHS 100 100
172 ARM 2325 99
173 CYBERSOURCE 157 99
174 DEERE 99 99
175 NEW YORK UNIVERSITY 97 97
176 APPSTEK 97 97
177 SAMSUNG AUSTIN SEMICONDUCTOR L.L.C 96 96
178 MEDTRONIC 96 96
179 THERMO FISHER SCIENTIFIC 95 95
180 EPAM SYSTEMS 1226 95
181 CITADEL SECURITIES AMERICAS 95 95
182 DELL PRODUCTS LP 95 95
183 WASHINGTON UNIVERSITY 95 95
184 UNIVERSITY OF FLORIDA 94 94
185 PIONEER CONSULTING 93 93
186 GENERAL HOSPITAL 93 93
187 ROBERT BOSCH 92 92
188 BATTELLE MEMORIAL INSTITUTE 92 92
189 CIGNA HEALTH & LIFE INSURANCE 91 91
190 ROCKWELL COLLINS 91 91
191 LENDINGCLUB 94 90
192 IBM INDIA PRIVATE 90 90
193 INTUITIVE SURGICAL OPERATIONS 90 90
194 HENRY FORD HEALTH SYSTEM 90 90
195 CREDIT KARMA 89 89
196 ILLUMINA 89 89
197 WOLTERS KLUWER UNITED STATES 89 89
198 UNIVERSITY OF IOWA 89 89
199 F5 NETWORKS 89 89
200 LARSEN & TOUBRO INFOTECH 101 88
201 UNIVERSITY OF CALIFORNIA LOS ANGELES 88 88
202 SPRINT 88 88
203 CBRE 92 88
204 UNIVERSITY OF UTAH 88 88
205 MOTOROLA SOLUTIONS 87 87
206 TRUSTEES OF PRINCETON UNIVERSITY 87 87
207 MUFG UNION BANK N.A 87 87
208 NETAPP 88 86
209 DELL PRODUCTS L.P 86 86
210 SAMSUNG SEMICONDUCTOR 1929 86
211 CITADEL ENTERPRISE AMERICAS 85 85
212 UNIVERSITY OF ALABAMA AT BIRMINGHAM 85 85
213 SYNOPSYS 3265 84
214 MICROCHIP 84 84
215 SYNECHRON 84 84
216 CITADEL AMERICAS 84 84
217 MICHIGAN STATE UNIVERSITY 83 83
218 FORTINET 232 83
219 DEVEREUX FOUNDATION 83 83
220 TRANSUNION 83 83
221 CA 363 83
222 CITRIX SYSTEMS 221 83
223 MERRILL LYNCH 82 82
224 BECTON DICKINSON 82 82
225 ATLASSIAN 82 82
226 NORTHWESTERN UNIVERSITY 82 82
227 EPSILON DATA MANAGEMENT 82 82
228 ELECTRONIC ARTS 82 82
229 REGENERON PHARMACEUTICALS 81 81
230 QUALCOMM ATHEROS 5453 81
231 DXC 2063 81
232 UNIVERSITY OF CHICAGO 80 80
233 BRIGHAM & WOMEN'S HOSPITAL 79 79
234 PINTEREST 79 79
235 GOLDMAN SACHS BANK USA 78 78
236 UT-BATTELLE LLC (OAK RIDGE NATIONAL LABO 78 78
237 RANDSTAD TECHNOLOGIES 77 77
238 MARKIT NORTH AMERICA 77 77
239 NCR 249 77
240 CYPRESS SEMICONDUCTOR 1681 76
241 UNIVERSITY OF CALIFORNIA SAN DIEGO 76 76
242 OKTA 76 76
243 BAYLOR COLLEGE OF MEDICINE 76 76
244 CHILDREN'S HOSPITAL 75 75
245 DELOITTE TRANSACTIONS & BUSINESS ANALYTI 225 75
246 UNIVERSITY OF CALIFORNIA DAVIS 75 75
247 UNIVERSITY OF MINNESOTA 75 75
248 YALE UNIVERSITY 74 74
249 EMORY UNIVERSITY 74 74
250 EVERCORE PARTNERS SERVICES EAST 74 74
251 HERBALIFE INTERNATIONAL OF AMERICA 73 73
252 NTT DATA 73 73
253 CARDINAL HEALTH 73 73
254 RBC CAPITAL MARKETS 123 73
255 ASURION 72 72
256 CLOUDERA 72 72
257 GE HEALTHCARE IITS USA 72 72
258 UNIVERSITY OF COLORADO 72 72
259 MCKESSON 71 71
260 MENTOR GRAPHICS 1655 71
261 CGI TECHNOLOGIES & SOLUTIONS 471 70
262 EQUINIX 70 70
263 MASSACHUSETTS INSTITUTE OF 70 70
264 ONETRUST 70 70
265 NATIONWIDE INSURANCE 69 69
266 WIPRO 111 69
267 TEXAS A&M UNIVERSITY 69 69
268 PENNSYLVANIA STATE UNIVERSITY 69 69
269 DISH NETWORK 69 69
270 UNIVERSITY OF SOUTHERN CALIFORNIA 68 68
271 KEYSIGHT TECHNOLOGIES 1174 67
272 FUJITSU AMERICA 123 67
273 CURATORS OF THE UNIVERSITY OF MISSOURI 67 67
274 UNIVERSITY OF CALIFORNIA BERKELEY 67 67
275 BRISTOL-MYERS SQUIBB 67 67
276 EXPRESS SCRIPTS 75 67
277 EXLSERVICE.COM 66 66
278 UNIVERSITY OF WISCONSIN SYSTEM 66 66
279 QUICKEN LOANS 66 66
280 KOHN PEDERSEN FOX ASSOCIATES PC 66 66
281 ARCADIS U.S 66 66
282 ELLIE MAE 65 65
283 UNIVERSITY OF TEXAS AT AUSTIN 65 65
284 UNIVERSITY OF CONNECTICUT 65 65
285 RSM US 65 65
286 SEMICONDUCTOR COMPONENTS INDUSTRIES 160 65
287 UATC 972 64
288 CORNELL UNIVERSITY 64 64
289 DANA-FARBER CANCER INSTITUTE 63 63
290 BRIDGEWATER ASSOCIATES LP 63 63
291 BANK OF NEW YORK MELLON 63 63
292 ASTRAZENECA PHARMACEUTICALS LP 63 63
293 HULU 62 62
294 SCHNEIDER ELECTRIC USA 62 62
295 NIAGARA BOTTLING 62 62
296 JUNIPER NETWORKS (US) 74 62
297 WEILL CORNELL MEDICAL COLLEGE 62 62
298 UNIVERSITY OF WASHINGTON 62 62
299 MEDLINE INDUSTRIES 62 62
300 CLIENT NETWORK 62 62
[1] "Search CASE_STATUS for CERTIFIED"
[1] "Search Secondary Sites Only"
[1] "Group by EMPLOYER_NAME2"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 110,746"
[1] "SUM(APPLICATIONS) = 84,191"
[1] "NUMBER OF ROWS = 14,587"
[1] "MEDIAN(LOW_WAGE) = NULL"
[1] "MEAN(LOW_WAGE) = NA"
[1] ""
EMPLOYER_NAME2 WORKERS APPLICATIONS
1 WELLS FARGO 1583 1467
2 ANTHEM 1157 1070
3 APPLE 1217 1044
4 AMERICAN EXPRESS 962 861
5 VERIZON 926 801
6 AT&T 877 770
7 FORD MOTOR 1105 694
8 BANK OF AMERICA 670 651
9 CITIGROUP 667 643
10 GOOGLE 662 557
11 CAPITAL ONE 598 541
12 FANNIE MAE 671 507
13 WALMART 617 486
14 CVS HEALTH 513 485
15 FIDELITY INVESTMENTS 664 439
16 COMCAST 577 434
17 CISCO SYSTEMS 481 430
18 KAISER PERMANENTE 865 387
19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
20 NIKE 518 351
21 CHARTER COMMUNICATIONS 436 340
22 FEDEX 391 337
23 DISCOVER 346 337
24 PNC BANK 1456 333
25 JP MORGAN CHASE 313 299
26 HOME DEPOT 309 299
27 JOHNSON & JOHNSON 360 294
28 CIGNA 571 289
29 CHARLES SCHWAB 488 287
30 MICROSOFT 344 281
31 HUMANA 349 276
32 VERIZON SOURCING 436 272
33 UNITED AIRLINES 534 271
34 MERCK 288 257
35 CVS PHARMACY 287 246
36 METLIFE 452 243
37 CENTENE 247 238
38 NORTHERN TRUST 241 228
39 SUNTRUST BANKS 283 225
40 KROGER 341 220
41 GENERAL ELECTRIC 229 220
42 AT & T 338 213
43 EQUIFAX 258 209
44 VANGUARD 257 209
45 FORUM CAPITAL MARKETS LLC (DBA WELLS FAR 207 207
46 CATERPILLAR 232 207
47 T-MOBILE 266 200
48 FACEBOOK 279 199
49 AMERICAN AIRLINES 254 196
50 PFIZER 416 195
51 STATE FARM MUTUAL AUTOMOBILE INSURANCE 233 194
52 METROPOLITAN LIFE INSURANCE 220 193
53 T-MOBILE USA 238 192
54 COMCAST CABLE COMMUNICATIONS MANAGEMENT 236 192
55 HEALTH CARE SERVICE 245 188
56 TRAVELERS 184 180
57 TOYOTA 346 172
58 ABBVIE 206 171
59 CUMMINS 172 170
60 DELOITTE CONSULTING 195 164
61 EXPRESS SCRIPTS 164 164
62 GAP 292 164
63 STATE STREET BANK & TRUST 216 163
64 HARTFORD 168 163
65 BOEING 192 159
66 LIBERTY MUTUAL INSURANCE 609 158
67 CHEVRON 203 157
68 NATIONWIDE MUTUAL INSURANCE 155 155
69 BEST BUY 159 153
70 PAYPAL 275 153
71 FARMERS INSURANCE GROUP 176 153
72 SPRINT 152 152
73 FISERV 199 152
74 SOUTHWEST AIRLINES 239 150
75 GILEAD SCIENCES 164 149
76 ALLY FINANCIAL 244 149
77 WELLS FARGO BANK 280 148
78 MORGAN STANLEY 156 147
79 TOYOTA MOTOR NORTH AMERICA 227 147
80 VERIZON COMMUNICATIONS 217 145
81 PEPSICO 148 143
82 JPMORGAN CHASE 261 142
83 WELLS FARGO BANK N.A 277 140
84 3M 152 138
85 VANGUARD GROUP 144 137
86 ALLSTATE INSURANCE 218 136
87 MOLINA HEALTHCARE 143 134
88 STATE FARM 306 132
89 ONCOR ELECTRIC DELIVERY 146 131
90 PACIFIC GAS & ELECTRIC 140 131
91 WALGREENS 134 129
92 INTEL 220 129
93 TRAVELERS INDEMNITY 130 126
94 FREDDIE MAC 128 123
95 AETNA 124 122
96 CAPITAL GROUP COMPANIES 212 122
97 MASTERCARD 325 120
98 VERIZON WIRELESS 130 120
99 AMERISOURCEBERGEN 125 120
100 WALGREEN 117 117
101 SOUTHERN CALIFORNIA EDISON 166 117
102 NATIONWIDE INSURANCE 116 116
103 COMCAST CABLE COMMUNICATIONS 115 115
104 CISCO 237 113
105 PRUDENTIAL FINANCIAL 158 113
106 CARDINAL HEALTH 120 113
107 STATE FARM INSURANCE 113 111
108 ABBOTT LABORATORIES 120 110
109 FIAT CHRYSLER AUTOMOBILES 260 108
110 ERNST & YOUNG 108 107
111 UNITED PARCEL SERVICE 106 106
112 HORIZON BLUE CROSS BLUE SHIELD OF NEW JE 105 105
113 CHARTER COMMUNICATIONS OPERATING 115 102
114 MEDTRONIC 144 101
115 EBAY 130 101
116 JP MORGAN CHASE BANK N.A 104 98
117 AMERICAN INTERNATIONAL GROUP 97 97
118 DUKE ENERGY 97 97
119 CREDIT SUISSE 107 97
120 WORLD BANK GROUP 96 96
121 MARRIOTT INTERNATIONAL 112 96
122 BLUE SHIELD OF CALIFORNIA 127 95
123 FCA US 214 93
124 7-ELEVEN 102 92
125 MCKESSON 97 92
126 EDWARD JONES 102 92
127 GOLDMAN SACHS 96 91
128 NATIONAL INSTITUTES OF HEALTH 105 91
129 COX COMMUNICATIONS 91 91
130 TJX COMPANIES 106 91
131 NISSAN NORTH AMERICA 100 91
132 BANK OF NEW YORK MELLON 90 90
133 ADP 90 88
134 JP MORGAN CHASE BANK NATIONAL ASSOCIATIO 88 88
135 DELOITTE 87 87
136 CENTURYLINK 86 86
137 PNC BANK NATIONAL ASSOCIATION 85 85
138 HEWLETT PACKARD ENTERPRISE 210 85
139 SYNCHRONY FINANCIAL 85 85
140 UNITED HEALTH GROUP 89 84
141 STATE OF CALIFORNIA 84 84
142 WAL-MART STORES 84 84
143 CITIZENS BANK 113 84
144 PRICEWATERHOUSECOOPERS 114 83
145 ELI LILLY 118 83
146 DELTA AIR LINES 83 83
147 APPLIED MATERIALS 83 83
148 INTUIT 147 82
149 CONDUENT 105 82
150 STATE STREET 82 82
151 CITICORP NORTH AMERICA 100 82
152 MUFG UNION BANK N.A 104 81
153 AMERIPRISE FINANCIAL 83 81
154 OPTUM 100 80
155 KEYBANK NATIONAL ASSOCIATION 84 80
156 BNSF RAILWAY 89 79
157 FLORIDA BLUE 79 79
158 TRUIST FINANCIAL 78 78
159 PNC 420 76
160 EMBLEM HEALTH 76 76
161 CITIBANK 77 75
162 MIRACLE SOFTWARE SYSTEMS 152 74
163 GE HEALTHCARE 73 73
164 BLUE CROSS BLUE SHIELD OF MICHIGAN 73 73
165 LINCOLN FINANCIAL GROUP 91 73
166 FLORIDA POWER & LIGHT 72 72
167 T-MOBILE US 72 72
168 DXC 72 72
169 KOHL'S DEPARTMENT STORES 83 72
170 M&T BANK 99 72
171 ROCKWELL AUTOMATION 71 71
172 FIDELITY 85 70
173 GENENTECH 72 70
174 US BANK 69 69
175 CHANGE HEALTHCARE 69 69
176 THOMSON REUTERS 69 69
177 UNITED SERVICES AUTOMOBILE ASSOCIATION ( 99 69
178 SEI INVESTMENTS 92 67
179 FINRA 66 66
180 CALIBER HOME LOANS 81 66
181 AMGEN 80 66
182 ADVANTASURE 66 66
183 CHUBB 65 65
184 NORTHWESTERN MUTUAL LIFE 101 65
185 STRYKER 90 64
186 DELTA AIRLINES 64 64
187 PRINCIPAL FINANCIAL GROUP 69 64
188 NBC UNIVERSAL 82 63
189 SAMSUNG ELECTRONICS AMERICA 63 63
190 T ROWE PRICE 65 63
191 MUFG UNION BANK 62 62
192 HOME DEPOT U.S.A 148 61
193 BECTON DICKINSON 65 61
194 WALMART STORES 63 61
195 JUNIPER NETWORKS 61 61
196 BRANCH BANKING & TRUST 60 60
197 COCA-COLA 60 60
198 QUEST DIAGNOSTICS 80 60
199 CELGENE 59 59
200 GENERAL MOTORS 64 59
201 CITI GROUP 59 59
202 LPL FINANCIAL 58 58
203 AMAZON 67 58
204 JPMORGAN CHASE BANK N.A 57 57
205 PROCTER & GAMBLE 99 57
206 TEACHERS INSURANCE & ANNUITY ASSOCIATION 57 57
207 STANDARD INSURANCE 57 57
208 JOHN DEERE 56 56
209 NEW YORK LIFE INSURANCE 126 56
210 DEUTSCHE BANK 102 56
211 BANK OF THE WEST 89 55
212 GEICO 55 55
213 COLLINS AEROSPACE 55 55
214 CITIBANK N.A 83 55
215 MASSACHUSETTS MUTUAL LIFE INSURANCE 102 54
216 FIFTH THIRD BANK 54 54
217 STATE COMPENSATION INSURANCE FUND 62 53
218 HONDA R&D AMERICAS 53 53
219 SAFEWAY 71 53
220 DAVITA 53 53
221 TRANSAMERICA 109 53
222 HALLIBURTON 53 53
223 CARGILL 78 53
224 IBM 53 53
225 PREMIER 53 53
226 VISA 54 52
227 LINCOLN NATIONAL 136 52
228 EQUINIX 61 52
229 UBS AG 88 52
230 BANK OF AMERICA N.A 97 52
231 MACY'S 70 52
232 TOYOTA MOTORS NORTH AMERICA 78 52
233 FRONTIER COMMUNICATIONS 51 51
234 BLUE CROSS BLUE SHIELD 60 51
235 AXA EQUITABLE LIFE INSURANCE 51 51
236 NAVISTAR 51 51
237 BIOGEN 51 51
238 METLIFE INSURANCE COMPANY OF CONNECTICUT 51 51
239 LIBERTY MUTUAL 123 50
240 EXXONMOBIL 56 50
241 PRIME THERAPEUTICS 50 50
242 AMERICAN ELECTRIC POWER 109 50
243 COSTCO WHOLESALE 59 50
244 MACY'S SYSTEMS & 50 50
245 PHILLIPS 66 49 49
246 INFOSYS 54 49
247 VOLKSWAGEN GROUP OF AMERICA 49 49
248 TEACHERS INSURANCE & ANNUITY ASSOCIATION 49 49
249 TD AMERITRADE 48 48
250 STAPLES 48 48
251 GOLDMAN SACHS GROUP 66 48
252 USAA ACCEPTANCE 48 48
253 STARBUCKS 47 47
254 HP 110 47
255 MAYO CLINIC 47 47
256 AETNA LIFE INSURANCE 47 47
257 COX AUTOMOTIVE 52 47
258 DUN & BRADSTREET 47 47
259 BP CORPORATION NORTH AMERICA 83 47
260 SCHLUMBERGER 57 46
261 EXPRESS SCRIPTS HOLDING 46 46
262 EMBLEMHEALTH 46 46
263 CAREFIRST BLUECROSS BLUESHIELD 49 45
264 WILLIAMS SONOMA 54 45
265 HCA - INFORMATION TECHNOLOGY & 55 45
266 FIRST DATA 45 45
267 HCL AMERICA 45 45
268 FARMERS INSURANCE 202 45
269 WALT DISNEY 54 45
270 SYSCO 53 44
271 ADVANCE AUTO PARTS 49 44
272 UBS 77 44
273 DAIMLER TRUCKS NORTH AMERICA 44 44
274 EXELON 80 44
275 PEARSON EDUCATION 44 44
276 MOODY'S 90 44
277 THERMO FISHER SCIENTIFIC 92 43
278 COTIVITI 43 43
279 HONDA NORTH AMERICA 58 43
280 SPRINT/UNITED MANAGEMENT 43 43
281 PEARSON 45 43
282 BNY MELLON 86 43
283 VERIZON DATA 43 43
284 FIRST REPUBLIC BANK 57 43
285 HERTZ 53 43
286 TRACTOR SUPPLY 43 43
287 VERIZON CORPORATE SERVICES GROUP 43 43
288 PITNEY BOWES 43 43
289 BOSTON SCIENTIFIC 47 42
290 KPMG 42 42
291 MICRON 44 42
292 NORTHWESTERN MUTUAL LIFE INSURANCE 42 42
293 KPS 51 42
294 TIFFANY 47 42
295 STATE OF MICHIGAN 49 41
296 SILICON VALLEY BANK 43 41
297 KEURIG DR PEPPER 41 41
298 INTERNATIONAL BUSINESS MACHINES 41 41
299 MARSH & MCLENNAN COMPANIES 41 41
300 WALMART LABS 41 41
Note: Secondary Employers denote when workers will be placed at a secondary location.
In this case, field SECONDARY ENTITY is set to Y as explained in this File Structure file and
EMPLOYER_NAME2 above will be set to the contents of field SECONDARY ENTITY BUSINESS NAME.
Primary Employers denote when workers will NOT be placed at a secondary location.
For more information, see section titled "Finding the Names of Companies where H-1B Holders are Working, even if they're Employed by a Another Company, FY 2020" at http://econdataus.com/h1b_states.htm.
Source: OFLC Performance Data (click Disclosure Data tab and go to section
"Latest Quarterly Updates"), 2020, Q2
R is a language and environment for statistical computing and graphics. One benefit of R is that it's often possible to analyze data with relatively little code. The following code shows the first step in replicating the first 20 lines in the table in the prior section:
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(CASE_STATUS == "Certified") %>%
filter(SECONDARY_ENTITY == "Y") %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS), desc(WORKERS))
print(head(as.data.frame(oo), 20))
On the left below is the resulting output. To the right of it are the first 20 lines from the prior section:
DATA GENERATED BY CODE ABOVE FIRST 20 LINES FROM PRIOR SECTION
------------------------------------------------------------------------------ -----------------------------------------------------------------
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS EMPLOYER_NAME2 WORKERS APPLICATIONS
1 Wells Fargo 969 926 1 WELLS FARGO 1583 1467
2 Ford Motor Company 967 606 2 ANTHEM 1157 1070
3 Verizon 673 554 3 APPLE 1217 1044
4 Bank of America 505 491 4 AMERICAN EXPRESS 962 861
5 WELLS FARGO 471 448 5 VERIZON 926 801
6 Fannie Mae 592 428 6 AT&T 877 770
7 Apple Inc. 456 421 7 FORD MOTOR 1105 694
8 CVS Health 407 379 8 BANK OF AMERICA 670 651
9 Capital One 386 359 9 CITIGROUP 667 643
10 Kaiser Permanente 828 350 10 GOOGLE 662 557
11 Fidelity Investments 530 314 11 CAPITAL ONE 598 541
12 PNC Bank 1412 306 12 FANNIE MAE 671 507
13 Anthem, Inc. 321 295 13 WALMART 617 486
14 American Express 307 286 14 CVS HEALTH 513 485
15 Apple, Inc. 337 265 15 FIDELITY INVESTMENTS 664 439
16 Comcast 373 255 16 COMCAST 577 434
17 Walmart 328 237 17 CISCO SYSTEMS 481 430
18 AT&T Services Inc 229 229 18 KAISER PERMANENTE 865 387
19 American Express Travel Related Services Company, Inc. 238 227 19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
20 VERIZON 228 222 20 NIKE 518 351
As can be seen, Wells Fargo is listed on line 1 as above but the counts are much lower. In addition, the companies listed on lines 2 and 3 of the prior section (ANTHEM and APPLE) don't show up until lines 13 and 7, respectively. Part of the problem can be seen to be that lines 1 and 5 are Wells Fargo and WELLS FARGO, respectively. The following code adds a line (in red) to convert all of the employer names to uppercase.
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(CASE_STATUS == "Certified") %>%
filter(SECONDARY_ENTITY == "Y") %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_to_upper(SECONDARY_ENTITY_BUSINESS_NAME)) %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS), desc(WORKERS))
print(head(as.data.frame(oo), 20))
On the left below is the resulting output. To the right of it are the first 20 lines from the prior section:
DATA GENERATED BY CODE ABOVE FIRST 20 LINES FROM PRIOR SECTION
------------------------------------------------------ -----------------------------------------------------------------
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS EMPLOYER_NAME2 WORKERS APPLICATIONS
1 WELLS FARGO 1451 1380 1 WELLS FARGO 1583 1467
2 VERIZON 907 782 2 ANTHEM 1157 1070
3 FORD MOTOR COMPANY 1061 673 3 APPLE 1217 1044
4 BANK OF AMERICA 658 643 4 AMERICAN EXPRESS 962 861
5 FANNIE MAE 668 504 5 VERIZON 926 801
6 APPLE INC. 509 474 6 AT&T 877 770
7 CAPITAL ONE 485 458 7 FORD MOTOR 1105 694
8 CVS HEALTH 485 457 8 BANK OF AMERICA 670 651
9 FIDELITY INVESTMENTS 631 415 9 CITIGROUP 667 643
10 AMERICAN EXPRESS 428 405 10 GOOGLE 662 557
11 KAISER PERMANENTE 864 386 11 CAPITAL ONE 598 541
12 WALMART 463 368 12 FANNIE MAE 671 507
13 COMCAST 486 363 13 WALMART 617 486
14 CITIGROUP 367 357 14 CVS HEALTH 513 485
15 ANTHEM, INC. 359 333 15 FIDELITY INVESTMENTS 664 439
16 PNC BANK 1452 329 16 COMCAST 577 434
17 ANTHEM 318 291 17 CISCO SYSTEMS 481 430
18 APPLE, INC. 353 281 18 KAISER PERMANENTE 865 387
19 CHARTER COMMUNICATIONS 264 260 19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
20 JP MORGAN CHASE 262 248 20 NIKE 518 351
As can be seen, WELLS FARGO is listed on line 1 as in the prior section but the counts are now closer. However, the companies listed on lines 2 and 3 of the prior section (ANTHEM and APPLE) don't show up until lines 15 and 6, respectively. The following code adds a line (in red) to look at all of the employer names (converted to uppercase) that contain ANTHEM.
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(CASE_STATUS == "Certified") %>%
filter(SECONDARY_ENTITY == "Y") %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_to_upper(SECONDARY_ENTITY_BUSINESS_NAME)) %>%
filter(str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'ANTHEM')) %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS), desc(WORKERS))
print(head(as.data.frame(oo), 20))
Following is the resultant output:
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS
1 ANTHEM, INC. 387 359
2 ANTHEM 331 304
3 ANTHEM INC 255 247
4 ANTHEM INC. 161 135
5 ANTHEM, INC 51 51
6 ANTHEM BLUE CROSS BLUE SHIELD 16 12
7 ANTHEM CAREMORE 11 11
8 ANTHEM INC., 8 8
9 ANTHEM CAREMORE INTEGRATIO 6 6
10 ANTHEM/CTS 6 6
11 CVS ANTHEM 6 6
12 SIGMA PETROLEUM INC DBA ANTHEM OIL RIALTO 6 6
13 ANTHEM INC. 5 5
14 ANTHEM DIGITAL 5 5
15 ANTHEM BCBS 4 4
16 ANTHEM BLUE CROSS AND BLUE SHIELD 4 4
17 ANTHEM INC,. 3 3
18 ANTHEM,INC 3 3
19 ANTHEM/AMERIGROUP 3 3
20 ANTHEM INC AMERIGROUP 2 2
As can be seen, there are multiple slight variations in the employer name given for ANTHEM. For example, there's versions with the following variations of INC appended to ANTHEM: [INC|INC.|, INC|, INC.|INC,.]. Changing the word ANTHEM to APPLE in the added line in red above results in the following output:
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS 1 APPLE INC. 509 474 2 APPLE, INC. 353 281 3 APPLE INC 214 162 4 APPLE 112 98 5 APPLE, INC 21 21 6 APPLE CORPORATION 3 3 7 DR PEPPER SNAPPLE GROUP 3 3 8 APPLE INC 2 2 9 APPLE ARQUES 1 1 10 APPLE CAMPUS 3 1 1 11 APPLE CENTRAL AND WOLFE CAMPUS 1 1 12 APPLE COMPUTER INC 1 1 13 APPLE COMPUTERS INC 1 1 14 APPLE CORP. 1 1 15 APPLE INC 1 1 16 APPLE,INC 1 1 17 APPLE,INC. 1 1 18 APPLEXUS TECHNOLOGIES LLC 1 1 19 DR PEPPER SNAPPLE GROUP INC 1 1 20 HOGARTH/APPLE 1 1Again, there are several slight variations of APPLE followed by INC. There's no way to tell whether or not these variations were added on purpose, perhaps to make the number of H-1B that they requested look smaller. In any event, this would suggest that it would be very helpful if companies were required to use just one variation of their name. The following lines (in red) can be added to the code to combine most variations of an appended INC.
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(CASE_STATUS == "Certified") %>%
filter(SECONDARY_ENTITY == "Y") %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_to_upper(SECONDARY_ENTITY_BUSINESS_NAME)) %>%
#filter(str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'APPLE')) %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_replace(SECONDARY_ENTITY_BUSINESS_NAME,"\\.","")) %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_replace(SECONDARY_ENTITY_BUSINESS_NAME,",","")) %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_replace(SECONDARY_ENTITY_BUSINESS_NAME," INC$","")) %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS), desc(WORKERS))
print(head(as.data.frame(oo), 20))
Following is the resultant output:
DATA GENERATED BY CODE ABOVE FIRST 20 LINES FROM PRIOR SECTION
------------------------------------------------------ -----------------------------------------------------------------
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS EMPLOYER_NAME2 WORKERS APPLICATIONS
1 WELLS FARGO 1454 1383 1 WELLS FARGO 1583 1467
2 ANTHEM 1148 1061 2 ANTHEM 1157 1070
3 APPLE 1209 1036 3 APPLE 1217 1044
4 VERIZON 925 800 4 AMERICAN EXPRESS 962 861
5 FORD MOTOR COMPANY 1061 673 5 VERIZON 926 801
6 BANK OF AMERICA 658 643 6 AT&T 877 770
7 FANNIE MAE 668 504 7 FORD MOTOR 1105 694
8 WALMART 615 484 8 BANK OF AMERICA 670 651
9 CVS HEALTH 504 476 9 CITIGROUP 667 643
10 CAPITAL ONE 485 458 10 GOOGLE 662 557
11 AT&T SERVICES 466 441 11 CAPITAL ONE 598 541
12 FIDELITY INVESTMENTS 659 434 12 FANNIE MAE 671 507
13 CISCO SYSTEMS 481 430 13 WALMART 617 486
14 AMERICAN EXPRESS 430 407 14 CVS HEALTH 513 485
15 CITIGROUP 399 389 15 FIDELITY INVESTMENTS 664 439
16 KAISER PERMANENTE 865 387 16 COMCAST 577 434
17 COMCAST 494 371 17 CISCO SYSTEMS 481 430
18 NIKE 514 347 18 KAISER PERMANENTE 865 387
19 CHARTER COMMUNICATIONS 432 336 19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
20 PNC BANK 1452 329 20 NIKE 518 351
As can be seen, Wells Fargo, Anthem, and Apple are now the top 3 as in the prior section and the totals are much closer. However, many of the employer names differ after that. The following code duplicates all of the processing that is done be the application:
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
xx <- dd %>%
filter(CASE_STATUS == "Certified") %>%
filter(SECONDARY_ENTITY == "Y")
names(xx)[names(xx) == "SECONDARY_ENTITY_BUSINESS_NAME"] <- "EMPLOYER_NAME2"
ignore <- c("case","comma","period","the","and","blanks")
trailer <- c("INC","INCORPORATED","LLC","LLP","LTD","LIMITED","N A","NA",
"& CO","& COMPANY", "CORPORATE SERVICES","FINANCIAL SERVICES",
"CO","COMPANY","CORP","CORPORATION",
"FINANCIAL SERVICES GROUP","TRAVEL RELATED SERVICES",
"SERVICES","TECHNOLOGY")
for (i in ignore){
if (i == "case") xx$EMPLOYER_NAME2 <- toupper(xx$EMPLOYER_NAME2)
if (i == "comma") xx$EMPLOYER_NAME2 <- gsub("[,]$", "", xx$EMPLOYER_NAME2)
if (i == "comma") xx$EMPLOYER_NAME2 <- gsub("[,]", " ", xx$EMPLOYER_NAME2)
if (i == "period") xx$EMPLOYER_NAME2 <- gsub("[.]$", "", xx$EMPLOYER_NAME2)
if (i == "period") xx$EMPLOYER_NAME2 <- gsub("[.][ ]", " ", xx$EMPLOYER_NAME2)
if (i == "the") xx$EMPLOYER_NAME2 <- gsub("^THE ", "", xx$EMPLOYER_NAME2)
if (i == "and") xx$EMPLOYER_NAME2 <- gsub(" AND ", " & ", xx$EMPLOYER_NAME2)
if (i == "blanks") xx$EMPLOYER_NAME2 <- trimws(gsub("[ ]+", " ", xx$EMPLOYER_NAME2))
}
for (i in trailer){
xx$EMPLOYER_NAME2 <- gsub(paste0(" ",i,"$"), "", xx$EMPLOYER_NAME2)
}
oo <- xx %>%
group_by(EMPLOYER_NAME2) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS), desc(WORKERS))
print(head(as.data.frame(oo), 20))
Following is the resultant output:
DATA GENERATED BY CODE ABOVE FIRST 20 LINES FROM PRIOR SECTION
-------------------------------------------------------------- -----------------------------------------------------------------
EMPLOYER_NAME2 WORKERS APPLICATIONS EMPLOYER_NAME2 WORKERS APPLICATIONS
1 WELLS FARGO 1583 1467 1 WELLS FARGO 1583 1467
2 ANTHEM 1157 1070 2 ANTHEM 1157 1070
3 APPLE 1217 1044 3 APPLE 1217 1044
4 AMERICAN EXPRESS 962 861 4 AMERICAN EXPRESS 962 861
5 VERIZON 926 801 5 VERIZON 926 801
6 AT&T 877 770 6 AT&T 877 770
7 FORD MOTOR 1105 694 7 FORD MOTOR 1105 694
8 BANK OF AMERICA 670 651 8 BANK OF AMERICA 670 651
9 CITIGROUP 667 643 9 CITIGROUP 667 643
10 GOOGLE 662 557 10 GOOGLE 662 557
11 CAPITAL ONE 598 541 11 CAPITAL ONE 598 541
12 FANNIE MAE 671 507 12 FANNIE MAE 671 507
13 WALMART 617 486 13 WALMART 617 486
14 CVS HEALTH 513 485 14 CVS HEALTH 513 485
15 FIDELITY INVESTMENTS 664 439 15 FIDELITY INVESTMENTS 664 439
16 COMCAST 577 434 16 COMCAST 577 434
17 CISCO SYSTEMS 481 430 17 CISCO SYSTEMS 481 430
18 KAISER PERMANENTE 865 387 18 KAISER PERMANENTE 865 387
19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374 19 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
20 NIKE 518 351 20 NIKE 518 351
As can be seen, the top 20 employer names are now identical to what they were in the prior section. It should be noted that the above rules will not be able to combine all variations of an employer name. For example, most misspellings are likely impossible to catch via general rules. Still, if one is focusing on a specific company, it's often possible to search for many misspellings by searching for a unique substring of the employer name and then searching for those matches which do not match the full employer name. For example, the following code will find employer names that contain "FARGO" but don't contain "WELLS FARGO".
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(SECONDARY_ENTITY == "Y") %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_to_upper(SECONDARY_ENTITY_BUSINESS_NAME)) %>%
filter(str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'FARGO')) %>%
filter(!str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'WELLS FARGO')) %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS))
print(head(as.data.frame(oo), 200))
Following is the resultant output:
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS
1 WELLSFARGO 32 32
2 FORUM CAPITAL MARKETS LLC (DBA WELL FARGO) 2 2
3 COGNIZANT / WELLSFARGO 1 1
4 ETTAIN AT WELL FARGO 1 1
5 WELL FARGO 1 1
6 WELL FARGO BANK 1 1
7 WELL FARGO COMMUNITY BANKING 1 1
8 WELLFARGO 1 1
9 WELLS-FARGO BANK, N.A. 1 1
10 WELLS FARGO 1 1
11 WELLSFARGO ADVISORS 1 1
12 WELLSFARGO BANK 1 1
13 WELLSFARGO BANK N.A 1 1
14 WELLSFARGO BANK NA 1 1
15 WELLSFARGO COMMUNITY BANKING 1 1
16 WELLSFARGO FINANCIAL SERVICES 1 1
As can be seen, the misspellings of WELLS FARGO appear to include WELLSFARGO, WELLFARGO, WELL FARGO, and WELLS-FARGO. Of course, there's always a possibility that FARGO is misspelled. The following code which changes "FARGO" to "WELLS " searches for that:
library("tidyverse")
library("readxl")
# Download the latest H-1B disclosure file to the local directory from the following URL:
# https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2020/H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx
if (!exists("dd")){
dd <- read_xlsx("H-1B_H-1B1_E-3_Disclosure_Data_FY2020_Q2.xlsx", guess_max = 272089)
}
oo <- dd %>%
filter(SECONDARY_ENTITY == "Y") %>%
mutate(SECONDARY_ENTITY_BUSINESS_NAME = str_to_upper(SECONDARY_ENTITY_BUSINESS_NAME)) %>%
filter(str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'WELLS ')) %>%
filter(!str_detect(SECONDARY_ENTITY_BUSINESS_NAME, 'WELLS FARGO')) %>%
group_by(SECONDARY_ENTITY_BUSINESS_NAME) %>%
summarize(WORKERS = sum(TOTAL_WORKER_POSITIONS), APPLICATIONS = n()) %>%
arrange(desc(APPLICATIONS))
print(head(as.data.frame(oo), 200))
Following is the resultant output:
SECONDARY_ENTITY_BUSINESS_NAME WORKERS APPLICATIONS 1 WELLS FARGO 1 1 2 WELLS FRGO BANK, N.A. 1 1 3 WELLS VEHICLE ELECTRONICS 1 1As can be seen, a single misspellings of WELLS FRGO is caught in the second line. The first line contains a double-space between WELLS and FARGO and would have been caught by the final code shown previously which converts all multiple spaces to a single space. The third line obviously refers to another company.
[1] "Search CASE_STATUS for CERTIFIED"
[1] "Group by EMPLOYER_NAME2"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 426,203"
[1] "SUM(APPLICATIONS) = 257,283"
[1] "NUMBER OF ROWS = 38,382"
[1] "MEDIAN(LOW_WAGE) = NULL"
[1] "MEAN(LOW_WAGE) = NA"
[1] ""
EMPLOYER_NAME2 WORKERS APPLICATIONS
1 QUALCOMM TECHNOLOGIES 29737 458
2 DELOITTE CONSULTING 9071 4273
3 ORACLE AMERICA 8733 363
4 GOOGLE 7158 7053
5 NVIDIA 6954 285
6 APPLE 6888 2908
7 FACEBOOK 6594 2519
8 CISCO SYSTEMS 6274 1116
9 COGNIZANT TECHNOLOGY SOLUTIONS US 5521 5521
10 AMAZON.COM 5467 4783
11 QUALCOMM ATHEROS 5453 81
12 ERNST & YOUNG U.S 5113 5113
13 WESTERN DIGITAL TECHNOLOGIES 4960 165
14 MICROSOFT 4564 4414
15 SERVICENOW 4401 239
16 MCKINSEY & COMPANY INC UNITED STATES 4024 261
17 SYNOPSYS 3266 85
18 DELOITTE & TOUCHE 2741 893
19 GILEAD SCIENCES 2529 255
20 UBER TECHNOLOGIES 2339 444
21 ARM 2325 99
22 QUALCOMM INNOVATION CENTER 2200 32
23 DXC 2135 153
24 INTEL 2036 778
25 SAMSUNG SEMICONDUCTOR 1931 88
26 HEWLETT PACKARD ENTERPRISE 1759 301
27 HGST 1753 50
28 CYPRESS SEMICONDUCTOR 1681 76
29 MENTOR GRAPHICS 1657 73
30 JPMORGAN CHASE 1613 1462
31 WAL-MART ASSOCIATES 1586 1586
32 ANTHEM 1583 1496
33 WELLS FARGO 1583 1467
34 QUALCOMM 1565 61
35 SALESFORCE.COM 1528 1316
36 PNC BANK 1456 333
37 WAYFAIR 1427 220
38 FORD MOTOR 1334 923
39 AMERICAN EXPRESS 1276 1124
40 DELOITTE TAX 1260 378
41 EPAM SYSTEMS 1227 96
42 KEYSIGHT TECHNOLOGIES 1194 79
43 COMPUTER SCIENCES 1181 46
44 CAPITAL ONE 1176 1119
45 WORKDAY 1050 130
46 PAYPAL 1027 731
47 INTERNATIONAL BUSINESS MACHINES 1027 1027
48 APPLIED MATERIALS 1023 198
49 LINKEDIN 1022 755
50 AT&T 986 879
51 UATC 972 64
52 VERIZON 932 807
53 GOLDMAN SACHS 914 909
54 HP 907 174
55 INFORMATICA 902 59
56 ITELLIGENCE 900 42
57 AMAZON WEB 874 852
58 KAISER PERMANENTE 865 387
59 INFOSYS 861 631
60 BLOOMBERG L.P 823 272
61 ADOBE 820 265
62 VMWARE 814 728
63 QUORA 800 24
64 AVAIL MEDSYSTEMS 750 15
65 OATH HOLDINGS 743 422
66 EBAY 722 577
67 INTUIT 713 385
68 CHARTER COMMUNICATIONS 708 612
69 KPMG 700 478
70 BANK OF AMERICA 677 658
71 BANK OF AMERICA N.A 675 630
72 FANNIE MAE 675 508
73 CITIGROUP 668 644
74 EXPEDIA 665 257
75 FIDELITY INVESTMENTS 664 439
76 CITY NATIONAL BANK 655 51
77 NIKE 637 470
78 NEW YORK CITY DEPARTMENT OF EDUCATION 617 39
79 WALMART 617 486
80 LIBERTY MUTUAL INSURANCE 613 162
81 NUTANIX 601 130
82 A.T KEARNEY 601 13
83 CHARLES SCHWAB 599 398
84 PALO ALTO NETWORKS 583 139
85 COMCAST 578 435
86 CIGNA 571 289
87 KITE PHARMA 563 31
88 CGI TECHNOLOGIES & SOLUTIONS 562 91
89 BLACKROCK FINANCIAL MANAGEMENT 559 559
90 BROADCOM 549 83
91 UNITED AIRLINES 540 277
92 FEDEX 534 480
93 IBM 514 514
94 CVS HEALTH 513 485
95 VISA TECHNOLOGY & OPERATIONS 502 356
96 SNOWFLAKE 496 24
97 UNITED SERVICES AUTOMOBILE ASSOCIATION 491 374
98 MACHINE ZONE 490 24
99 CADENCE DESIGN SYSTEMS 485 177
100 PNC 480 136
101 PRICEWATERHOUSECOOPERS 469 438
102 COMCAST CABLE COMMUNICATIONS 462 462
103 DOLBY LABORATORIES 457 26
104 METLIFE 452 243
105 PRICEWATERHOUSECOOPERS ADVISORY 440 440
106 MICRON 437 435
107 VERIZON SOURCING 436 272
108 PFIZER 435 214
109 CUMMINS 433 431
110 MORGAN STANLEY SERVICES GROUP 429 429
111 HOULIHAN LOKEY 426 18
112 MANHATTAN ASSOCIATES 425 47
113 CERNER 423 423
114 T-MOBILE USA 414 368
115 AMERICAN AIRLINES 412 354
116 HUMANA 412 307
117 ADP 409 305
118 STATE STREET BANK & TRUST 409 356
119 AMGEN 406 392
120 ACCENTURE 401 396
121 A10 NETWORKS 400 16
122 ADVANCED MICRO DEVICES 397 386
123 WELLS FARGO BANK N.A 396 259
124 CVS PHARMACY 390 349
125 JOHNSON & JOHNSON 376 310
126 FCA US 364 243
127 SUNPOWER 364 22
128 CA 363 83
129 PHILIPS NORTH AMERICA 363 28
130 EQUIFAX 362 313
131 ADVANTEST AMERICA 361 17
132 KROGER 354 233
133 OPTUM 352 332
134 JUNIPER NETWORKS 346 240
135 TOYOTA 346 172
136 DISCOVER 346 337
137 MACY'S SYSTEMS & 339 196
138 AT & T 338 213
139 HCL AMERICA 335 335
140 GAP 332 203
141 CAPGEMINI AMERICA 326 326
142 VISA U.S.A 326 268
143 MASTERCARD 325 120
144 CREDIT SUISSE SECURITIES (USA) 320 308
145 JP MORGAN CHASE 316 302
146 AGILENT TECHNOLOGIES 313 26
147 TESLA 309 309
148 HOME DEPOT 309 299
149 STATE FARM 306 132
150 GENERAL MOTORS 305 300
151 MAYO CLINIC 305 305
152 CITIBANK N.A 301 273
153 SNAP 291 119
154 SUNTRUST BANKS 291 233
155 BOSTON CONSULTING GROUP 289 289
156 PROGRESSIVE INSURANCE 289 39
157 GENERAL ELECTRIC 289 280
158 MERCK 288 257
159 CATERPILLAR 286 261
160 TREASURE DATA 281 14
161 WELLS FARGO BANK 280 148
162 MASTERCARD INTERNATIONAL 279 177
163 HEALTH CARE SERVICE 272 215
164 NORTHERN TRUST 271 258
165 MICRO FOCUS 267 34
166 ABBVIE 267 232
167 T-MOBILE 266 200
168 TATA CONSULTANCY 264 260
169 NCR 263 91
170 FIAT CHRYSLER AUTOMOBILES 260 108
171 VANGUARD 257 209
172 SOUTHWEST AIRLINES 257 168
173 YODLEE 255 15
174 SAP AMERICA 253 253
175 DFS 252 252
176 AT&T OFFICE 249 9
177 CENTENE 247 238
178 ALLY FINANCIAL 244 149
179 LUMENTUM OPERATIONS 244 26
180 BOFA SECURITIES 240 240
181 MEDTRONIC 240 197
182 SPRINT 240 240
183 EXPRESS SCRIPTS 239 231
184 STATE FARM MUTUAL AUTOMOBILE INSURANCE 237 198
185 CISCO 237 113
186 COMCAST CABLE COMMUNICATIONS MANAGEMENT 236 192
187 CHEVRON 235 189
188 SLALOM 235 152
189 JM FAMILY ENTERPRISES 234 26
190 FORTINET 232 83
191 BAIN 232 58
192 TOYOTA MOTOR NORTH AMERICA 227 147
193 DELOITTE TRANSACTIONS & BUSINESS ANALYTI 225 75
194 SONY INTERACTIVE ENTERTAINMENT 223 156
195 AUTODESK 223 156
196 NATSOFT 223 223
197 ALLSTATE INSURANCE 223 141
198 CITRIX SYSTEMS 222 84
199 RIVIAN AUTOMOTIVE 221 202
200 MINDTREE 220 220
201 METROPOLITAN LIFE INSURANCE 220 193
202 MORGAN STANLEY 217 208
203 VERIZON COMMUNICATIONS 217 145
204 EMC 216 216
205 BARCLAYS 214 214
206 PAYCOM PAYROLL 213 53
207 CAPITAL GROUP COMPANIES 212 122
208 BOEING 208 170
209 WAYMO 207 203
210 FORUM CAPITAL MARKETS LLC (DBA WELLS FAR 207 207
211 ZURICH NORTH AMERICA 207 13
212 GUMGUM 206 10
213 TWILIO 203 58
214 FARMERS INSURANCE 202 45
215 COX AUTOMOTIVE 201 196
216 BEST BUY 200 194
217 COOPERATIVE REGIONS OF ORGANIC PRODUCER 200 5
218 FISERV 199 152
219 PACIFIC LIFE INSURANCE 199 27
220 SCHLUMBERGER 198 187
221 UCHICAGO ARGONNE 197 45
222 CARDINAL HEALTH 193 186
223 DELOITTE SERVICES LP 193 43
224 DISCOVER PRODUCTS 192 192
225 MUFG UNION BANK N.A 191 168
226 VERIZON DATA 190 190
227 TWITTER 190 161
228 U.S BANK NATIONAL ASSOCIATION 190 190
229 FIDELITY TECHNOLOGY GROUP 188 188
230 THERMO FISHER SCIENTIFIC 187 138
231 NATIONWIDE INSURANCE 185 185
232 LOWE'S COMPANIES 184 184
233 VANGUARD GROUP 184 177
234 TRAVELERS 184 180
235 NORDSTROM 183 183
236 UNIVERSITY OF MICHIGAN 181 181
237 PROGRESSIVE CASUALTY INSURANCE 177 61
238 CSC COVANSYS 176 7
239 FARMERS INSURANCE GROUP 176 153
240 BOXY CHARM 175 4
241 MIRACLE SOFTWARE SYSTEMS 173 90
242 TECH MAHINDRA (AMERICAS) 172 172
243 MOLINA HEALTHCARE 171 162
244 BDO USA 170 170
245 YELP 170 56
246 SPLUNK 170 117
247 MATHWORKS 170 170
248 TEXAS INSTRUMENTS 169 160
249 AKAMAI TECHNOLOGIES 168 168
250 UBS BUSINESS SOLUTIONS US 168 161
251 MCKESSON 168 163
252 HARTFORD 168 163
253 AECOM TECHNICAL 167 167
254 LYFT 167 157
255 SOUTHERN CALIFORNIA EDISON 167 118
256 PEPSICO 165 160
257 TRUIST BANK 164 117
258 IQVIA 162 153
259 ERICSSON 162 162
260 LINCOLN NATIONAL 160 76
261 SEMICONDUCTOR COMPONENTS INDUSTRIES 160 65
262 3M 159 145
263 GOVERNMENT EMPLOYEES INSURANCE 159 28
264 AIRBNB 158 156
265 PRUDENTIAL FINANCIAL 158 113
266 CYBERSOURCE 157 99
267 MASTECH DIGITAL TECHNOLOGIES INC A MASTE 156 26
268 FIDELITY MANAGEMENT & RESEARCH 156 156
269 NATIONWIDE MUTUAL INSURANCE 155 155
270 TARGET ENTERPRISE 153 153
271 BANK OF NEW YORK MELLON 153 153
272 SQUARE 152 152
273 AVAYA 152 37
274 NEW YORK LIFE INSURANCE 152 82
275 PENSANDO SYSTEMS 151 19
276 PACIFIC GAS & ELECTRIC 150 141
277 DELL USA L.P 149 143
278 ELI LILLY 148 113
279 HOME DEPOT U.S.A 148 61
280 BECTON DICKINSON 147 143
281 ZILLOW 147 147
282 ABBOTT LABORATORIES 147 137
283 NXP USA 146 146
284 STELLUS TECHNOLOGIES 146 8
285 ONCOR ELECTRIC DELIVERY 146 131
286 ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI 144 144
287 7-ELEVEN 144 134
288 AMERISOURCEBERGEN 143 138
289 MEMORIAL SLOAN KETTERING CANCER CENTER 140 140
290 BLUE SHIELD OF CALIFORNIA 140 108
291 MASSACHUSETTS MUTUAL LIFE INSURANCE 139 91
292 DROPBOX 139 139
293 UNIVERSITY OF CALIFORNIA SAN FRANCISCO 138 138
294 HOME DEPOT PRODUCT AUTHORITY 138 138
295 MARRIOTT INTERNATIONAL 137 121
296 INDEED 137 137
297 MOTOROLA SOLUTIONS 136 126
298 PROKARMA 136 136
299 DEERE 136 127
300 DOLBY LABORATORIES LICENSING 135 6
[1] "Search CASE_STATUS for CERTIFIED"
[1] "Sort by TOTAL_WORKERS, Descending"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 426,203"
[1] "SUM(APPLICATIONS) = 0"
[1] "NUMBER OF ROWS = 257,283"
[1] "MEDIAN(LOW_WAGE) = 100,000"
[1] "MEAN(LOW_WAGE) = 262,695"
[1] ""
CASE_STATUS EMPLOYER_NAME JOB_TITLE WORKERS PW_WAGE_LEVEL WAGE_RATE_FROM WAGE_PW WORKSITE_CITY STATE
1 Certified APPLE Software Developer, Systems Software 275 II 122408.00 1.0000 CUPERTINO CALIFORNIA
2 Certified APPLE Software Developer, Systems Software 275 II 122408.00 1.0000 CUPERTINO CALIFORNIA
3 Certified APPLE Software Developer, Systems Software 200 III 147534.00 1.0000 CUPERTINO CALIFORNIA
4 Certified QUALCOMM TECHNOLOGIES Systems Test Engineer 200 II 96616.00 1.0000 SAN DIEGO CALIFORNIA
5 Certified APPLE Software Developer, Applications 175 II 108784.00 1.0000 CUPERTINO CALIFORNIA
6 Certified APPLE Software Developer, Applications 175 III 131726.00 1.0000 CUPERTINO CALIFORNIA
7 Certified UBER TECHNOLOGIES SOFTWARE ENGINEER 175 II 119122.00 1.0000 SAN FRANCISCO CALIFORNIA
8 Certified APPLE SOFTWARE DEVELOPER, APPLICATIONS 175 II 108874.00 1.0008 CUPERTINO CALIFORNIA
9 Certified APPLE Software Developer, Applications 175 III 131726.00 1.0000 CUPERTINO CALIFORNIA
10 Certified APPLE Electrical Engineer 150 III 132746.00 1.0000 CUPERTINO CALIFORNIA
11 Certified APPLE Electrical Engineer 150 II 106330.00 1.0000 CUPERTINO CALIFORNIA
12 Certified UATC SOFTWARE ENGINEER 150 II 119122.00 1.0000 SAN FRANCISCO CALIFORNIA
13 Certified SYNOPSYS R&D Engineer 150 137201.00 1.0000 MOUNTIAN VIEW CALIFORNIA
14 Certified SYNOPSYS Applications Engineer 150 125494.00 1.0000 MOUNTAIN VIEW CALIFORNIA
15 Certified APPLE ELECTRICAL ENGINEER 150 II 106330.00 1.0000 CUPERTINO CALIFORNIA
16 Certified APPLE Electronics Engineer, Except Computer 125 II 111634.00 1.0000 CUPERTINO CALIFORNIA
17 Certified APPLE Electronics Engineer, Except Computer 125 III 134597.00 1.0000 CUPERTINO CALIFORNIA
18 Certified UBER TECHNOLOGIES DATA ANALYST (DATA SCIENTIST) 125 II 97906.00 1.0000 SAN FRANCISCO CALIFORNIA
19 Certified APPLE Electronics Engineer, Except Computer 125 II 111634.00 1.0000 CUPERTINO CALIFORNIA
20 Certified AMAZON.COM SOFTWARE DEVELOPMENT ENGINEER I 121 I 93184.00 1.0000 SEATTLE WASHINGTON
21 Certified APPLIED MATERIALS Process Engineer 115 116939.00 1.0000 SANTA CLARA CALIFORNIA
22 Certified APPLE Software Developer, Systems Software 100 IV 172640.00 1.0000 CUPERTINO CALIFORNIA
23 Certified UBER TECHNOLOGIES SOFTWARE ENGINEER 100 III 144040.00 1.0000 SAN FRANCISCO CALIFORNIA
24 Certified UBER TECHNOLOGIES SENIOR SOFTWARE ENGINEER 100 II 119122.00 1.0000 SAN FRANCISCO CALIFORNIA
25 Certified UBER TECHNOLOGIES SOFTWARE ENGINEER 100 II 108784.00 1.0000 PALO ALTO CALIFORNIA
26 Certified UBER TECHNOLOGIES SENIOR SOFTWARE ENGINEER 100 II 108784.00 1.0000 PALO ALTO CALIFORNIA
27 Certified UBER TECHNOLOGIES DATA ANALYST (DATA SCIENTIST) 100 II 89773.00 1.0000 PALO ALTO CALIFORNIA
28 Certified UATC SOFTWARE ENGINEER 100 III 144040.00 1.0000 SAN FRANCISCO CALIFORNIA
29 Certified UATC SENIOR SOFTWARE ENGINEER 100 II 119122.00 1.0000 SAN FRANCISCO CALIFORNIA
30 Certified UATC DATA ANALYST (DATA SCIENTIST) 100 II 97906.00 1.0000 SAN FRANCISCO CALIFORNIA
31 Certified QUALCOMM TECHNOLOGIES ASICS Engineer 100 II 108971.00 1.0000 SAN DIEGO CALIFORNIA
32 Certified QUALCOMM TECHNOLOGIES Staff Software Engineer 100 III 116646.00 1.0000 SAN DIEGO CALIFORNIA
33 Certified QUALCOMM TECHNOLOGIES Senior ASICs Engineer 100 II 108971.00 1.0000 SAN DIEGO CALIFORNIA
34 Certified EXPEDIA SOFTWARE DEVELOPMENT ENGINEER 100 98421.00 1.0000 SEATTLE WASHINGTON
35 Certified QUALCOMM ATHEROS Senior Software Engineer 100 II 122408.00 1.0000 SANTA CLARA CALIFORNIA
36 Certified QUALCOMM ATHEROS Senior Asics Engineer 100 II 111634.00 1.0000 SANTA CLARA CALIFORNIA
37 Certified QUALCOMM TECHNOLOGIES Senior Staff Software Applications Engin 100 IV 135800.00 1.0616 SAN DIEGO CALIFORNIA
38 Certified QUALCOMM ATHEROS Senior Staff Systems Engineer 100 IV 147306.00 1.0000 SAN DIEGO CALIFORNIA
39 Certified QUALCOMM INNOVATION CENTER Staff Software Engineer 100 III 116646.00 1.0000 SAN DIEGO CALIFORNIA
40 Certified QUALCOMM TECHNOLOGIES Senior Staff Modem Engineer 100 IV 166100.00 1.1276 SAN DIEGO CALIFORNIA
41 Certified QUALCOMM TECHNOLOGIES Senior Staff Modem Software Engineer 100 IV 152400.00 1.1149 SAN DIEGO CALIFORNIA
42 Certified QUALCOMM TECHNOLOGIES Modem Software Engineer 100 II 96616.00 1.0000 SAN DIEGO CALIFORNIA
43 Certified QUALCOMM TECHNOLOGIES Senior Hardware Applications Engineer 100 II 108971.00 1.0000 SAN DIEGO CALIFORNIA
44 Certified QUALCOMM TECHNOLOGIES Modem Engineer 100 II 108971.00 1.0000 SAN DIEGO CALIFORNIA
45 Certified QUALCOMM TECHNOLOGIES Senior Software Engineer 100 II 96616.00 1.0000 SAN DIEGO CALIFORNIA
46 Certified QUALCOMM TECHNOLOGIES Senior Staff Software Engineer 100 IV 138600.00 1.0139 SAN DIEGO CALIFORNIA
47 Certified QUALCOMM TECHNOLOGIES Senior Staff Systems Test Engineer 100 IV 140200.00 1.0256 SAN DIEGO CALIFORNIA
48 Certified QUALCOMM TECHNOLOGIES Software Engineer 100 II 96616.00 1.0000 SAN DIEGO CALIFORNIA
49 Certified QUALCOMM TECHNOLOGIES Senior Staff Systems Engineer 100 IV 147306.00 1.0000 SAN DIEGO CALIFORNIA
50 Certified QUALCOMM TECHNOLOGIES Senior Systems Test Engineer 100 II 97700.00 1.0112 SAN DIEGO CALIFORNIA
[1] "Search CASE_STATUS for CERTIFIED"
[1] "Sort by WAGE_PW, Descending"
[1] ""
[1] "H-1B DISCLOSURE DATA, FY 2020"
[1] "(CASE_STATUS=CERTIFIED)"
[1] ""
[1] "SUM(TOTAL_WORKERS) = 426,203"
[1] "SUM(APPLICATIONS) = 0"
[1] "NUMBER OF ROWS = 257,283"
[1] "MEDIAN(LOW_WAGE) = 100,000"
[1] "MEAN(LOW_WAGE) = 262,695"
[1] ""
CASE_STATUS EMPLOYER_NAME JOB_TITLE WORKERS PREVAILING_WAGE PW_WAGE_LEVEL WAGE_RATE_FROM WAGE_PW WORKSITE_CITY STATE
1 Certified PAYPAL DATA Product Strategist 1 104499.00 IV 1.204781e+09 11529.1122 TEXAS TEXAS
2 Certified EMETEORS Software Developer 1 39.17 II 9.000000e+04 2297.6768 WINDSOR MILLS MARYLAND
3 Certified UNIVERSITY PRIMARY CARE PRACTICES PHYSICIAN 1 100.00 5 2.099968e+05 2099.9680 ASHLAND OH
4 Certified PAYPAL DATA Product Strategist 1 92955.00 I 1.204781e+07 129.6090 AUSTIN TEXAS
5 Certified LOWE'S COMPANIES IT SOFTWARE ENGINEER 1 89918.00 II 1.130000e+07 125.6701 CHARLOTTE NORTH CAROLINA
6 Certified NXP USA Customer Application Support 1 111634.00 II 1.339197e+07 119.9632 SAN JOSE CALIFORNIA
7 Certified UNIVERSITY OF ALABAMA AT BIRMINGHAM Assistant Professor 1 35.65 II 7.820000e+02 21.9355 BIRMINGHAM ALABAMA
8 Certified BANK OF NEW YORK MELLON Global Head of Investor Relations 1 254405.00 IV 4.000000e+06 15.7230 NEW YORK NEW YORK
9 Certified STUDIO GANG ARCHITECTS Junior Architechtural Designer 1 45510.00 I 6.800000e+05 14.9418 CHICAGO ILLINOIS
10 Certified COMMONWEALTH HEALTHCARE PHYSICIAN (PSYCHIATRIST) 1 15080.00 2.000000e+05 13.2626 SAIPAN NORTHERN MARIANA ISLANDS
11 Certified NERDWALLET FINANCIAL ANALYST 1 75421.00 I 9.500000e+05 12.5960 SAN FRANCISCO CALIFORNIA
12 Certified CLEVELAND CLINIC Staff Gastroenterologist 1 43784.00 II 5.500000e+05 12.5617 CLEVELAND OHIO
13 Certified NORTH MISSISSIPPI MEDICAL CENTER CARDIOLOGIST & ELECTROPHYSIOLOGIST 1 40290.00 II 5.000000e+05 12.4100 TUPELO MISSISSIPPI
14 Certified UBS SECURITIES DIRECTOR, ALM BUSINESS PROCESS ANALYST 1 122200.00 III 1.500000e+06 12.2750 STAMFORD CONNECTICUT
15 Certified ITECH US Software Engineer 1 87339.00 III 1.065000e+06 12.1939 KANSAS CITY MISSOURI
16 Certified INNOVIS HEALTH Interventional Cardiologist 1 58386.00 II 7.100000e+05 12.1604 FARGO NORTH DAKOTA
17 Certified IOWA PHYSICIANS CLINIC MEDICAL FOUNDATIO CARDIOLOGIST 1 58053.00 II 7.000000e+05 12.0579 DES MOINES IOWA
18 Certified AKORN SENIOR ANALYTICAL SCIENTST I 1 76752.00 II 9.100523e+05 11.8570 CRANBURY NEW JERSEY
19 Certified AMAZON.COM Program Manager III 1 113443.00 IV 1.315000e+06 11.5917 SEATTLE WASHINGTON
20 Certified INFOGAIN TECHNICAL PROJECT MANAGER 1 109554.00 II 1.267580e+06 11.5704 MOUNTAIN VIEW CALIFORNIA
21 Certified AMAZON.COM SENIOR MANAGER PROGRAM MANAGMENT 1 139048.00 III 1.600000e+06 11.5068 SEATTLE WASHINGTON
22 Certified FACEBOOK Software Engineer 1 168958.00 IV 1.940668e+06 11.4861 MENLO PARK CALIFORNIA
23 Certified SAPIENT Senior Interactive Developer L2 1 117021.00 III 1.325883e+06 11.3303 NEW YORK NEW YORK
24 Certified OHIO STATE UNIVERSITY Professor - Physician 1 63900.00 I 7.230000e+05 11.3146 COLUMBUS OHIO
25 Certified DULUTH CLINIC Cardiologist-EP 1 58386.00 II 6.600000e+05 11.3041 DULUTH MINNESOTA
26 Certified WALTER P MOORE & ASSOCIATES Graduate Engineer 1 2316.80 I 2.557693e+04 11.0398 AUSTIN TEXAS
27 Certified PROMETRIKA Statistical Applications Developer 1 91874.00 II 1.000000e+06 10.8845 CAMBRIDGE MASSACHUSETTS
28 Certified INFRRD Software Developer 1 93891.00 II 1.000000e+06 10.6506 LOS ANGELES CALIFORNIA
29 Certified MEDICAL INSTRUMENT DEVELOPMENT LABORATOR R&D Engineer 1 79789.00 I 8.300000e+05 10.4024 SAN LEANDRO CALIFORNIA
30 Certified ARGUS INFORMATION & ADVISORY Senior Manager 1 97906.00 II 1.007000e+06 10.2854 SAN FRANCISCO CALIFORNIA
31 Certified FOOTPRINTS EDUCATION Instructional Coordinator 1 50856.00 I 5.160000e+05 10.1463 SUNNYVALE CALIFORNIA
32 Certified COGNIZANT TECHNOLOGY SOLUTIONS US Senior Systems Analyst JC60 1 59238.00 II 6.000000e+05 10.1286 BENTONVILLE ARKANSAS
33 Certified KINFOLK CONSTRUCTION MANAGER 1 148574.00 IV 1.500000e+06 10.0960 VENICE CALIFORNIA
34 Certified ALTRU HEALTH SYSTEM Neurosurgeon 1 89440.00 IV 9.000000e+05 10.0626 GRAND FORKS NORTH DAKOTA
35 Certified PAYPAL Lead Decision Scientist 1 134202.00 III 1.350000e+06 10.0595 NEW YORK NEW YORK
36 Certified DELL MARKETING L.P Software Engineer 2 1 94738.00 9.519008e+05 10.0477 SANTA CLARA CALIFORNIA
37 Certified BRILLIO Test Lead 1 109554.00 II 1.100000e+06 10.0407 PALO ALTO CALIFORNIA
38 Certified XORIANT SOFTWARE ENGINEER 1 91686.00 II 9.200000e+05 10.0342 ORLANDO FLORIDA
39 Certified CLIENTSERVER TECHNOLOGY SOLUTIONS Programmer Analyst 1 72509.00 II 7.260000e+05 10.0126 SAN ANTONIO TEXAS
40 Certified HP Software Designer 5 94765.00 II 9.477650e+05 10.0012 SAN DIEGO CALIFORNIA
41 Certified DELTA REGIONAL MEDICAL CENTER GENERAL SURGEON 1 40290.00 II 4.000000e+05 9.9280 GREENVILLE MISSISSIPPI
42 Certified AURORA MEDICAL GROUP Gastroenterologist 1 58386.00 II 5.564000e+05 9.5297 SHEBOYGAN WISCONSIN
43 Certified UNIVERSITY HOSPITALS MEDICAL GROUP Cardiothoracic Transplant Director 1 78978.00 IV 7.500000e+05 9.4963 CLEVELAND OHIO
44 Certified UNIVERSITY OF PITTSBURGH PHYSICIANS Assistant Professor 1 49.31 III 4.642800e+02 9.4155 PITTSBURGH PENNSYLVANIA
45 Certified INDIANA BIOSCIENCES RESEARCH INSTITUTE Senior Executive for Innovation and Disc 1 74027.00 IV 6.825000e+05 9.2196 INDIANAPOLIS INDIANA
46 Certified INDIANA BIOSCIENCES RESEARCH INSTITUTE Senior Executive for Innovation and Disc 1 74027.00 IV 6.825000e+05 9.2196 INDIANAPOLIS INDIANA
47 Certified UNIVERSITY OF FLORIDA PROGRAM DIRECTOR AND CLINICAL PROFESSOR 1 94950.00 IV 8.560000e+05 9.0153 GAINESVILLE FLORIDA
48 Certified UNIVERSITY OF FLORIDA PROGRAM DIRECTOR AND CLINICAL PROFESSOR 1 94950.00 IV 8.560000e+05 9.0153 GAINESVILLE FLORIDA
49 Certified INNOVIS HEALTH Psychiatrist 1 28.07 II 2.500000e+02 8.9063 FARGO NORTH DAKOTA
50 Certified UNIVERSITY OF PITTSBURGH Assistant Professor 1 24880.00 I 2.196000e+05 8.8264 PITTSBURGH PENNSYLVANIA
51 Certified ALLEN MEMORIAL HOSPITAL Interventional Radiologist 1 58053.00 II 5.100000e+05 8.7851 WATERLOO IOWA
52 Certified NETFLIX Computer Graphics Pipeline Lead 1 71178.00 IV 6.000000e+05 8.4296 LOS ANGELES CALIFORNIA
53 Certified MISSISSIPPI BAPTIST MEDICAL CENTER INTERNAL MEDICINE PHYSICIAN-NOCTURNIST 1 35818.00 II 3.000000e+05 8.3757 JACKSON MISSISSIPPI
54 Certified SOUTH CENTRAL REGIONAL MEDICAL CENTER GENERAL SURGEON 1 35818.00 II 3.000000e+05 8.3757 LAUREL MISSISSIPPI
55 Certified PRICEWATERHOUSECOOPERS Advisory Principal 1 98072.00 IV 8.047500e+05 8.2057 SAN DIEGO CALIFORNIA
56 Certified GROUP HEALTH PLAN Gastroenterologist 1 58386.00 II 4.750000e+05 8.1355 ST. PAUL MINNESOTA
57 Certified CLEVELAND CLINIC Associate Staff 1 43784.00 II 3.500000e+05 7.9938 CLEVELAND OHIO
58 Certified NEW YORK UNIVERSITY SCHOOL OF MEDICINE Division Chief of Pediatric Orthopedic S 1 101379.00 IV 8.075000e+05 7.9652 NEW YORK NEW YORK
59 Certified NEW YORK UNIVERSITY SCHOOL OF MEDICINE Division Chief of Pediatric Orthopedic S 1 101379.00 IV 8.075000e+05 7.9652 NEW YORK NEW YORK
60 Certified AURORA MEDICAL GROUP Critical Care Medicine Physician 1 58386.00 II 4.600000e+05 7.8786 GREEN BAY WISCONSIN
61 Certified AURORA MEDICAL GROUP Critical Care Medicine Physician 1 58386.00 II 4.599840e+05 7.8783 GREEN BAY WISCONSIN
62 Certified TALLAHASSEE MEMORIAL HEALTHCARE Physican 1 44658.00 IV 3.500000e+05 7.8373 TALLAHASSEE FLORIDA
63 Certified LSU HEALTH SCIENCES CENTER Associate Professor of Clinical Anesthes 1 52640.00 II 4.088890e+05 7.7676 SHREVEPORT LOUISIANA
64 Certified IOWA PHYSICIANS CLINIC MEDICAL FOUNDATIO General Surgeon 1 58053.00 II 4.500000e+05 7.7515 SIOUX CITY IOWA
65 Certified IOWA PHYSICIANS CLINIC MEDICAL FOUNDATIO Pulmonary/Critical Care Physician 1 58053.00 II 4.500000e+05 7.7515 VINTON IOWA
66 Certified SANFORD CLINIC NORTH Anesthesiologist 1 59946.00 II 4.614030e+05 7.6970 FARGO NORTH DAKOTA
67 Certified GOLDMAN SACHS GROUP MANAGING DIRECTOR 1 197142.00 IV 1.500000e+06 7.6087 NEW YORK NEW YORK
68 Certified UNIVERSITY OF FLORIDA PROGRAM DIRECTOR AND CLINICAL PROFESSOR 1 112653.00 IV 8.560000e+05 7.5986 GAINESVILLE FLORIDA
69 Certified HENRY FORD HEALTH SYSTEM Radiologist 1 56638.00 III 4.248000e+05 7.5003 DETROIT MICHIGAN
70 Certified UMASS MEMORIAL MEDICAL GROUP Internal Medicine Physician 1 54163.00 I 4.056980e+05 7.4903 WORCESTER MASSACHUSETTS
71 Certified AURORA MEDICAL GROUP Abdominal Transplant Surgeon 1 58386.00 II 4.350000e+05 7.4504 MILWAUKEE WISCONSIN
72 Certified NORTH MISSISSIPPI MEDICAL CENTER INTERNAL MEDICINE PHYSICIAN-HOSPITALIST 1 40290.00 II 3.000000e+05 7.4460 TUPELO MISSISSIPPI
73 Certified NETFLIX VP, HR Business Partner 1 163197.00 IV 1.200000e+06 7.3531 LOS ANGELES CALIFORNIA
74 Certified CRAVATH SWAINE & MOORE ATTORNEY/PARTNER 1 218046.00 IV 1.600000e+06 7.3379 NEW YORK NEW YORK
75 Certified HERBERT SMITH FREEHILLS NEW YORK Partner 1 218046.00 IV 1.586925e+06 7.2779 NEW YORK NEW YORK
76 Certified HERBERT SMITH FREEHILLS NEW YORK Partner 1 218046.00 IV 1.586925e+06 7.2779 NEW YORK NEW YORK
77 Certified CARNEGIE MELLON UNIVERSITY Assistant Professor of Business Technolo 1 24880.00 I 1.770000e+05 7.1141 PITTSBURGH PENNSYLVANIA
78 Certified DEUTSCHE BANK SECURITIES Managing Director 1 254405.00 IV 1.800000e+06 7.0753 NEW YORK NEW YORK
79 Certified TWEEDY BROWNE Analyst 1 122928.00 III 8.600000e+05 6.9960 STAMFORD CONNECTICUT
80 Certified OCHSNER CLINIC FOUNDATION Cardiology - Staff Physician 1 58386.00 II 4.000000e+05 6.8510 KENNER LOUISIANA
81 Certified DECATUR MEMORIAL HOSPITAL Cardiologist 1 87693.00 IV 6.000000e+05 6.8421 DECATUR ILLINOIS
82 Certified DEACONESS HOSPITAL Hospitalist 1 44034.00 I 3.000000e+05 6.8129 NEWBURGH INDIANA
83 Certified MEDICAL ONCOLOGY ASSOCIATES P.S Medical Oncologist Physician 1 65998.00 III 4.450000e+05 6.7426 SPOKANE WASHINGTON
84 Certified UNIVERSITY OF OKLAHOMA HEALTH SCIENCES C ASSISTANT PROFESSOR 1 55807.00 II 3.750000e+05 6.7196 OKLAHOMA CITY OKLAHOMA
85 Certified MAYO CLINIC Cardiologist (Senior Associate Consultan 1 87110.00 IV 5.852500e+05 6.7185 ROCHESTER MINNESOTA
86 Certified TEST Test Job 1 15080.00 1.000000e+05 6.6313 TEST CITY ALABAMA
87 Certified HENRY FORD HEALTH SYSTEM Gynecology Oncology Physician 1 56638.00 III 3.750000e+05 6.6210 DETROIT MICHIGAN
88 Certified INSURANCE SERVICES OFFICE QA Analyst III 1 16021.00 1.060210e+05 6.6176 JERSEY CITY NEW JERSEY
89 Certified UNIVERSITY OF OKLAHOMA HEALTH SCIENCES C ASSISTANT PROFESSOR 1 55807.00 II 3.687500e+05 6.6076 OKLAHOMA CITY OKLAHOMA
90 Certified PINE BELT MENTAL HEALTHCARE RESOURCES CHILD AND ADOLESCENT PSYCHIATRIST 1 35818.00 II 2.350000e+05 6.5609 HATTIESBURG MISSISSIPPI
91 Certified UNIVERSITY OF PITTSBURGH PHYSICIANS Clinical Assistant Professor- Radiology 1 26.01 IV 1.700000e+02 6.5359 COPLEY OHIO
92 Certified VIRGINIA MASON MEDICAL CENTER Gastrointestinal Medical Oncologist and 1 75213.00 IV 4.900000e+05 6.5148 SEATTLE WASHINGTON
93 Certified DEACONESS HOSPITAL Pulmonology/Critical Care Physician & Me 1 58386.00 II 3.750000e+05 6.4228 EVANSVILLE INDIANA
94 Certified HSHS MEDICAL GROUP Intensivist 1 61797.00 II 3.950000e+05 6.3919 SPRINGFIELD ILLINOIS
95 Certified HARTFORD HEALTHCARE MEDICAL GROUP Physician (Interventional and Non-Invasi 1 60736.00 I 3.840000e+05 6.3224 HARTFORD CONNECTICUT
96 Certified TRUSTEES OF THE UNIVERSITY OF PENNSYLVAN Assistant Professor 1 39510.00 I 2.482500e+05 6.2832 PHILADELPHIA PENNSYLVANIA
97 Certified HSHS MEDICAL GROUP Intensivist 1 61797.00 II 3.850000e+05 6.2301 SPRINGFIELD ILLINOIS
98 Certified CARILION MEDICAL CENTER Gastroenterologist 1 72592.00 IV 4.500000e+05 6.1990 ROANOKE VIRGINIA
99 Certified WILSON SONSINI GOODRICH & ROSATI PC Associate 1 49421.00 IV 3.050000e+05 6.1715 WASHINGTON DISTRICT OF COLUMBIA
100 Certified WEST VIRGINIA UNIVERSITY Assistant Professor (Internal Medicine) 1 62490.00 IV 3.840000e+05 6.1450 CHARLESTON WEST VIRGINIA