/estimate
POST /estimate
POST /estimateProduces a compensation estimate based on many optional factors.
Code Examples
curl --request POST \
--url https://api.lightcast.io/comp/estimate \
--header 'accept: application/json' \
--header 'authorization: Bearer <Access_Token>' \
--header 'content-type: application/json' \ Request Body Example
{
"msa": "42660",
"titles": [
"ETCC677E49FBA73537"
],
"keyword": "Hadoop OR Hive"
}Response Examples
{
"search_parameters": {
"keyword": "Hadoop OR Hive",
"socs": [
"15-1252"
],
"weight_field": "weight_v1",
"skills": [
"Java (Programming Language)"
],
"skills_operator": 0,
"companies": [],
"industries": [],
"ed_levels": [],
"experiences": [
-1
],
"percentiles": [
10,
25,
50,
75,
90
],
"geography": {
"type": "MSA",
"code": "42660",
"name": "Seattle-Tacoma-Bellevue, WA",
"abbr": "",
"counties": [
"53061",
"53033",
"53053"
]
}
},
"national_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 95008,
"hourly_salary": 45.67692307692307,
"observations": 226,
"observations_delta": 226
},
{
"percentile": 25,
"annual_salary": 124832,
"hourly_salary": 60.01538461538462,
"observations": 773,
"observations_delta": 547
},
{
"percentile": 50,
"annual_salary": 150880,
"hourly_salary": 72.53846153846153,
"observations": 1814,
"observations_delta": 1041
},
{
"percentile": 75,
"annual_salary": 185056,
"hourly_salary": 88.96923076923076,
"observations": 2951,
"observations_delta": 1137
},
{
"percentile": 90,
"annual_salary": 220256,
"hourly_salary": 105.8923076923077,
"observations": 3520,
"observations_delta": 569
}
],
"observations": 3767,
"bySocInfo": [
{
"soc": "15-1252",
"weighted": 16001
}
],
"log_issue_regionalization": false
},
"regional_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 124587,
"hourly_salary": 59.89750931173621,
"observations": 226,
"observations_delta": 226
},
{
"percentile": 25,
"annual_salary": 164737,
"hourly_salary": 79.20058764775021,
"observations": 773,
"observations_delta": 547
},
{
"percentile": 50,
"annual_salary": 191931,
"hourly_salary": 92.27454713875211,
"observations": 1814,
"observations_delta": 1041
},
{
"percentile": 75,
"annual_salary": 230372,
"hourly_salary": 110.7557064541301,
"observations": 2951,
"observations_delta": 1137
},
{
"percentile": 90,
"annual_salary": 234486,
"hourly_salary": 112.7337370118173,
"observations": 3520,
"observations_delta": 569
}
],
"observations": 0,
"bySocInfo": [],
"log_issue_regionalization": false
},
"national_employment": 1419522,
"regional_employment": 73957,
"socs_in_estimate": [
{
"soc": "15-1252",
"name": "Software Developers",
"national_employment": 1419522,
"regional_employment": 73957
}
],
"timings": {
"agnitio_national": 213,
"agnitio_regional": 192,
"gis": 0,
"elastic_1": 63,
"elastic_2": 13,
"total": 621
}
}{
"errors": [
"Not enough data to form an estimate (unweighted)"
]
}POST /estimate_by_experience
POST /estimate_by_experienceProduces multiple compensation estimates at once, once per year of experience.
Code Examples
curl --request POST \
--url https://api.lightcast.io/comp/estimate_by_experience \
--header 'accept: application/json' \
--header 'authorization: Bearer <Access_Token>' \
--header 'content-type: application/json' \ Request Body Example
{
"msa": "42660",
"titles": [
"ETCC677E49FBA73537"
],
"keyword": "Hadoop OR Hive",
"experiences": [
1,
3,
5,
10
]
}Response Examples
{
"search_parameters": {
"keyword": "Hadoop OR Hive",
"socs": [
"15-1252"
],
"weight_field": "weight_v1",
"skills": [
"Java (Programming Language)"
],
"skills_operator": 0,
"companies": [],
"industries": [],
"ed_levels": [],
"experiences": [
1,
3,
5,
10
],
"percentiles": [
10,
25,
50,
75,
90
],
"geography": {
"type": "MSA",
"code": "42660",
"name": "Seattle-Tacoma-Bellevue, WA",
"abbr": "",
"counties": [
"53061",
"53033",
"53053"
]
}
},
"national_employment": 1419522,
"regional_employment": 73957,
"socs_in_estimate": [
{
"soc": "15-1252",
"name": "Software Developers",
"national_employment": 1419522,
"regional_employment": 73957
}
],
"by_experience": [
{
"experience": 1,
"national_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 73056,
"hourly_salary": 35.12307692307692,
"observations": 39,
"observations_delta": 39
},
{
"percentile": 25,
"annual_salary": 90208,
"hourly_salary": 43.36923076923077,
"observations": 151,
"observations_delta": 112
},
{
"percentile": 50,
"annual_salary": 122848,
"hourly_salary": 59.06153846153846,
"observations": 722,
"observations_delta": 571
},
{
"percentile": 75,
"annual_salary": 145632,
"hourly_salary": 70.01538461538462,
"observations": 1612,
"observations_delta": 890
},
{
"percentile": 90,
"annual_salary": 183520,
"hourly_salary": 88.23076923076923,
"observations": 2903,
"observations_delta": 1291
}
],
"observations": 3767,
"bySocInfo": [
{
"soc": "15-1252",
"weighted": 16001
}
],
"log_issue_regionalization": false
},
"regional_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 95801,
"hourly_salary": 46.05793659774125,
"observations": 39,
"observations_delta": 39
},
{
"percentile": 25,
"annual_salary": 119045,
"hourly_salary": 57.23313421661313,
"observations": 151,
"observations_delta": 112
},
{
"percentile": 50,
"annual_salary": 156272,
"hourly_salary": 75.13085609027982,
"observations": 722,
"observations_delta": 571
},
{
"percentile": 75,
"annual_salary": 181294,
"hourly_salary": 87.16050839922985,
"observations": 1612,
"observations_delta": 890
},
{
"percentile": 90,
"annual_salary": 195377,
"hourly_salary": 93.93113203004098,
"observations": 2903,
"observations_delta": 1291
}
],
"observations": 0,
"bySocInfo": [],
"log_issue_regionalization": false
}
},
{
"experience": 3,
"national_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 79456,
"hourly_salary": 38.2,
"observations": 75,
"observations_delta": 75
},
{
"percentile": 25,
"annual_salary": 101024,
"hourly_salary": 48.56923076923077,
"observations": 347,
"observations_delta": 272
},
{
"percentile": 50,
"annual_salary": 131680,
"hourly_salary": 63.30769230769231,
"observations": 1104,
"observations_delta": 757
},
{
"percentile": 75,
"annual_salary": 164832,
"hourly_salary": 79.24615384615385,
"observations": 2152,
"observations_delta": 1048
},
{
"percentile": 90,
"annual_salary": 197600,
"hourly_salary": 95,
"observations": 3249,
"observations_delta": 1097
}
],
"observations": 3767,
"bySocInfo": [
{
"soc": "15-1252",
"weighted": 16001
}
],
"log_issue_regionalization": false
},
"regional_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 104193,
"hourly_salary": 50.09279744730247,
"observations": 75,
"observations_delta": 75
},
{
"percentile": 25,
"annual_salary": 133318,
"hourly_salary": 64.0954255841957,
"observations": 347,
"observations_delta": 272
},
{
"percentile": 50,
"annual_salary": 167507,
"hourly_salary": 80.53229299596288,
"observations": 1104,
"observations_delta": 757
},
{
"percentile": 75,
"annual_salary": 205195,
"hourly_salary": 98.65167628310985,
"observations": 2152,
"observations_delta": 1048
},
{
"percentile": 90,
"annual_salary": 210366,
"hourly_salary": 101.137705368004,
"observations": 3249,
"observations_delta": 1097
}
],
"observations": 0,
"bySocInfo": [],
"log_issue_regionalization": false
}
},
{
"experience": 5,
"national_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 92960,
"hourly_salary": 44.69230769230769,
"observations": 188,
"observations_delta": 188
},
{
"percentile": 25,
"annual_salary": 122848,
"hourly_salary": 59.06153846153846,
"observations": 722,
"observations_delta": 534
},
{
"percentile": 50,
"annual_salary": 144096,
"hourly_salary": 69.27692307692308,
"observations": 1508,
"observations_delta": 786
},
{
"percentile": 75,
"annual_salary": 176864,
"hourly_salary": 85.03076923076924,
"observations": 2609,
"observations_delta": 1101
},
{
"percentile": 90,
"annual_salary": 214496,
"hourly_salary": 103.1230769230769,
"observations": 3463,
"observations_delta": 854
}
],
"observations": 3767,
"bySocInfo": [
{
"soc": "15-1252",
"weighted": 16001
}
],
"log_issue_regionalization": false
},
"regional_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 121901,
"hourly_salary": 58.60635383987663,
"observations": 188,
"observations_delta": 188
},
{
"percentile": 25,
"annual_salary": 162119,
"hourly_salary": 77.941824142454,
"observations": 722,
"observations_delta": 534
},
{
"percentile": 50,
"annual_salary": 183301,
"hourly_salary": 88.12561734163326,
"observations": 1508,
"observations_delta": 786
},
{
"percentile": 75,
"annual_salary": 220174,
"hourly_salary": 105.852808157008,
"observations": 2609,
"observations_delta": 1101
},
{
"percentile": 90,
"annual_salary": 228354,
"hourly_salary": 109.7855933735597,
"observations": 3463,
"observations_delta": 854
}
],
"observations": 0,
"bySocInfo": [],
"log_issue_regionalization": false
}
},
{
"experience": 10,
"national_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 101024,
"hourly_salary": 48.56923076923077,
"observations": 347,
"observations_delta": 347
},
{
"percentile": 25,
"annual_salary": 131040,
"hourly_salary": 63,
"observations": 1048,
"observations_delta": 701
},
{
"percentile": 50,
"annual_salary": 161632,
"hourly_salary": 77.70769230769231,
"observations": 2072,
"observations_delta": 1024
},
{
"percentile": 75,
"annual_salary": 187232,
"hourly_salary": 90.01538461538462,
"observations": 3011,
"observations_delta": 939
},
{
"percentile": 90,
"annual_salary": 221536,
"hourly_salary": 106.5076923076923,
"observations": 3552,
"observations_delta": 541
}
],
"observations": 3767,
"bySocInfo": [
{
"soc": "15-1252",
"weighted": 16001
}
],
"log_issue_regionalization": false
},
"regional_estimate": {
"percentiles": [
{
"percentile": 10,
"annual_salary": 132476,
"hourly_salary": 63.69027851032375,
"observations": 347,
"observations_delta": 347
},
{
"percentile": 25,
"annual_salary": 172930,
"hourly_salary": 83.13929926109641,
"observations": 1048,
"observations_delta": 701
},
{
"percentile": 50,
"annual_salary": 205608,
"hourly_salary": 98.8502094587141,
"observations": 2072,
"observations_delta": 1024
},
{
"percentile": 75,
"annual_salary": 233081,
"hourly_salary": 112.0580388143032,
"observations": 3011,
"observations_delta": 939
},
{
"percentile": 90,
"annual_salary": 235849,
"hourly_salary": 113.3888800425412,
"observations": 3552,
"observations_delta": 541
}
],
"observations": 0,
"bySocInfo": [],
"log_issue_regionalization": false
}
}
],
"timings": {
"agnitio_national": 194,
"agnitio_regional": 188,
"gis": 0,
"elastic_1": 22,
"elastic_2": 14,
"total": 556
}
}{
"errors": [
"Not enough data to form an estimate (unweighted)"
]
}POST /by_msa
POST /by_msaTakes multiple MSA codes and produces an estimate for each. This is much faster than making many separate calls to /estimate. The response format is much more minimal than that of the other estimation endpoints to reduce data size.
Code Examples
curl --request POST \
--url https://api.lightcast.io/comp/by_msa \
--header 'accept: application/json' \
--header 'authorization: Bearer <Access_Token>' \
--header 'content-type: application/json' \ Request Body Example
{
"msas": [
"42660",
"12060",
"35620"
],
"titles": [
"ETCC677E49FBA73537"
],
"keyword": "Hadoop OR Hive"
}Response Examples
{
"by_msa": [
{
"msa": "42660",
"employment": 73957,
"median_hourly": 92.27454713875211,
"median_annual": 191931
},
{
"msa": "12060",
"employment": 37615,
"median_hourly": 71.54127665245586,
"median_annual": 148806
},
{
"msa": "35620",
"employment": 95289,
"median_hourly": 82.72424579330809,
"median_annual": 172066
}
]
}{
"errors": [
"Not enough data to form an estimate (unweighted)"
]
}