County intelligence

St. Charles County

Missouri (MO) · FIPS 29183 · 1,800 employers · 10,811 filings with wage data

Employers in St. Charles, MO filed 11,445 certified H-1B applications requesting 21,038 workers across 1,781 companies. The median offered wage is $85,925/yr. The largest filers are Wipro Limited, Mastercard International Incorporated and CSC Covansys Corporation. The displacement model assigns 26.5K worker-equivalent exposures to these filings.

Data current as of Sep 2, 2026

Filings & wages

Annual filing records and a county-level wage comparison.

Filing history

Annual DOL filing records. Workers requested are not confirmed hires.

02004006008001K1K1K2K2K2Kpeak 1K (2019)2007: 23 filings (23 workers)2008: 173 filings (488 workers)2009: 150 filings (1,086 workers)2010: 85 filings (727 workers)2011: 425 filings (1,341 workers)2012: 404 filings (2,186 workers)2013: 332 filings (1,101 workers)2014: 164 filings (469 workers)2015: 642 filings (1,303 workers)2016: 705 filings (1,000 workers)2017: 822 filings (1,301 workers)2018: 1,095 filings (1,811 workers)2019: 1,158 filings (1,652 workers)2020: 840 filings (1,525 workers)2021: 753 filings (1,030 workers)2022: 964 filings (1,114 workers)2023: 855 filings (1,041 workers)2024: 884 filings (993 workers)2025: 1,137 filings (1,226 workers)2026: 162 filings (162 workers)200720082009201020112012201320142015201620172018201920202021202220232024202520262007: 23 workers2008: 488 workers2009: 1,086 workers2010: 727 workers2011: 1,341 workers2012: 2,186 workers2013: 1,101 workers2014: 469 workers2015: 1,303 workers2016: 1,000 workers2017: 1,301 workers2018: 1,811 workers2019: 1,652 workers2020: 1,525 workers2021: 1,030 workers2022: 1,114 workers2023: 1,041 workers2024: 993 workers2025: 1,226 workers2026: 162 workersfilings
filingsworkers (scaled)
Inspect filing outcomes All available years and DOL statuses

Certified, denied, and withdrawn counts describe application decisions. They do not measure visas issued or workers hired.

Offered-wage distribution

Percentiles across 10,567 positive year-unit LCA offers, all outcomes and visa classes.

$57,392$75,546$93,700$111,854$130,008$85,925annual wage

Application outcomes all available years

  • Certified11,227 · 97.2%
  • Denied72 · 0.6%
  • Withdrawn256 · 2.2%
How this distribution is built Year-unit offers, all outcomes and visa classes

The distribution covers positive offers with wage unit Year, across all outcomes and visa classes. It differs from the certified H-1B summary cohort. It does not adjust for occupation, employer, or worksite mix.

Downstream impact

Conditional effects of this county's modeled displacement exposure.

Americans displaced (modeled estimate)

26,475

The math
Base (1 per certified worker)
+21,038
Wage-gap multiplier

9230 of 11445 filings below BLS median

+5,437
Total26,475

Σ workers×(1+wage_gap) + Σ WARN layoffs. The 1.0 base rate per certified H-1B worker request is a site model assumption. Wage gap multiplier = (BLS median − offered wage) / BLS median, applied only to filings offering less than the BLS median. Related research provides context, not validation of these exact coefficients. This is a modeled estimate, not a count of actual displacements.

Exposure method v1.2 · This is a modeled worker-equivalent count.

Modeled consequence estimates

Conditional impacts associated with modeled displacement

Explore St. Charles County’s scenarioEarnings · children · health · adjust the worker count

These are conditional population estimates scaled from St. Charles County's current modeled displacement count. They are not observed outcomes, a prediction about any person, or evidence that this entity caused displacement.

Exposure method v1.2 (stored with this aggregate) · benchmarked to the latest BLS survey. Consequence parameters v1.52; build v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1

Excess deaths over 20 years

Illustrative reference calculation · population applicability is not established

761.39

Range: 298.17 to 1,326.29

20-year reference scenario: high-seniority male displacement effect. This is not an expected count for an unknown population.

Source-profile mortality point (deaths)
761.392955647
No sustained excess from year 7 (deaths)
543.359736004

Declared structural comparison; not a confidence interval or a model probability.

Baseline population: US prime-age men (45-54).

Child lifetime earnings lost

Illustrative reference calculation · population applicability is not established

$12.7B

Range: $3.3B to $21.4B

Canadian father–son firm-closure effect, applied to a US male lifetime-earnings baseline in 2024 dollars. The reference result uses 2 children per worker.

Baseline population: US male median lifetime earnings.

The mortality effect comes from a high-seniority male study cohort. Treat the count as a reference scenario unless the population matches. A mixed population needs a reviewed transport rule.

The range is the engine's parameter-support envelope: it varies declared parameters only and adds none of the exposure input's uncertainty.

The math, limits, and citations

Illustrative reference calculation scaled by the supplied worker-equivalent exposure. Two children per worker; 20-year mortality follow-up. This does not establish that an entity caused these outcomes.

Input SHA-256: 65625244b6014b6429cf6d6fd7f3f525fdafb6dce287e996ad1a82b5db273d17

Excess deaths over 20 years: {"status":"illustrative_reference_calculation","eligible_for_public_headline":false,"target_population":null,"decision":null,"transport_assumptions":["high-tenure male mass-layoff cohort, ages 45–54","Pennsylvania early-1980s response transported to target place and calendar time","fixed baseline age rate over follow-up; cohort aging is not modeled"],"reason":"Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."}

Child lifetime earnings lost: {"status":"illustrative_reference_calculation","eligible_for_public_headline":false,"target_population":null,"decision":null,"transport_assumptions":["Canadian father-son firm-closure estimate transported to the target families","US male synthetic career earnings convert a relative adult earnings effect to dollars","lifetime dollars are undiscounted; this is not an annual loss"],"reason":"Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."}

Projection eligibility: {"child":{"status":"direct_estimate","eligible_for_validated_direct_contrast":true,"reason":"direct displacement-to-child adult earnings estimate; transport still requires an applicability decision"},"grandchild":{"status":"structural_projection","eligible_for_validated_direct_contrast":false,"reason":"combines a direct child estimate with an intergenerational persistence assumption; not an identified displacement intervention effect"},"greatgrandchild":{"status":"structural_projection","eligible_for_validated_direct_contrast":false,"reason":"repeats an intergenerational persistence assumption beyond the identification core"}}

Exposure source: {"source":"one-worker normalized reference input","method":"scale by the stored warehouse worker-equivalent exposure at read time"}

Exact values: excess deaths over 20 years 761.392955647 (range 298.171209231 to 1,326.29091027); child lifetime earnings lost $12,678,813,262.78 (range $3,293,198,250.07 to $21,405,788,625.47);

The displayed range is a parameter-support envelope, not a confidence interval.

Place reference: national reference.

Not included: exposure estimation error; baseline estimation error; unmodeled pathways.

Blocked model paths: local_service_jobs_lost: requires a documented net local loss of tradable jobs; worker displacement alone is not this exposure.

  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_peak; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offset_1; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offsets_2_3; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offsets_4_5; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_sustained; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Child lifetime earnings lost: oreopoulos2008 (displacement->child_earnings; EXACT) Study population: Canada 39k father-son pairs firm closures.
Scenario assumptions, sensitivity and source records

Outcome statistics use the displayed exposure. Baselines, coefficients, annual family schedules and component records retain their source normalization.

{
  "displayed_workers": 26475.195,
  "source_normalization_workers": 1,
  "applicability": {
    "excess_deaths": {
      "status": "illustrative_reference_calculation",
      "eligible_for_public_headline": false,
      "target_population": null,
      "decision": null,
      "transport_assumptions": [
        "high-tenure male mass-layoff cohort, ages 45–54",
        "Pennsylvania early-1980s response transported to target place and calendar time",
        "fixed baseline age rate over follow-up; cohort aging is not modeled"
      ],
      "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
    },
    "child_lifetime_earnings_lost_usd": {
      "status": "illustrative_reference_calculation",
      "eligible_for_public_headline": false,
      "target_population": null,
      "decision": null,
      "transport_assumptions": [
        "Canadian father-son firm-closure estimate transported to the target families",
        "US male synthetic career earnings convert a relative adult earnings effect to dollars",
        "lifetime dollars are undiscounted; this is not an annual loss"
      ],
      "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
    }
  },
  "target_population": null,
  "projection_eligibility": {
    "child": {
      "status": "direct_estimate",
      "eligible_for_validated_direct_contrast": true,
      "reason": "direct displacement-to-child adult earnings estimate; transport still requires an applicability decision"
    },
    "grandchild": {
      "status": "structural_projection",
      "eligible_for_validated_direct_contrast": false,
      "reason": "combines a direct child estimate with an intergenerational persistence assumption; not an identified displacement intervention effect"
    },
    "greatgrandchild": {
      "status": "structural_projection",
      "eligible_for_validated_direct_contrast": false,
      "reason": "repeats an intergenerational persistence assumption beyond the identification core"
    }
  },
  "child_applicability": {
    "source": "oreopoulos2008",
    "source_age_at_displacement": [
      10,
      14
    ],
    "source_child_sex": "Male",
    "source_parent_sex": "Male",
    "source_geography": "Canada",
    "source_event": "father firm closure 1980-1982",
    "target_child_profiles": null,
    "incompatible_children": [],
    "unknown_children": [],
    "source_income_quartile": null,
    "income_rank_definition": null,
    "eligible_for_reviewed_transport": false,
    "status": "unknown",
    "limitations": [
      "No response curve across child ages is identified by this narrow cohort.",
      "Income groups refer to father's average pre-displacement income in 1978-1979; target rank mapping requires a transport argument.",
      "A subgroup's nonsignificant coefficient is retained with its uncertainty, not replaced with zero."
    ]
  },
  "child_valuation": null,
  "assumptions": {
    "mortality_method": "odds_survival",
    "mortality_timing": "Source-offset profile: displacement, +1, +2–3, +4–5, and +6+; displacement is follow-up year 1, so offset +6 begins in follow-up year 7. Annual baseline rates use a constant-hazard rate-to-risk conversion; odds ratios modify annual risk, and survival compounds across phases. The selected baseline age rate is held fixed over the follow-up horizon.",
    "mortality_contract": {
      "method": "odds_survival",
      "timing": "source_profile",
      "baseline_conversion": "1-exp(-annual_rate)",
      "phases": [
        {
          "phase": "displacement",
          "start_offset": 0,
          "duration_years": 1,
          "first_follow_up_year": 1
        },
        {
          "phase": "offset_1",
          "start_offset": 1,
          "duration_years": 1,
          "first_follow_up_year": 2
        },
        {
          "phase": "offsets_2_3",
          "start_offset": 2,
          "duration_years": 2,
          "first_follow_up_year": 3
        },
        {
          "phase": "offsets_4_5",
          "start_offset": 4,
          "duration_years": 2,
          "first_follow_up_year": 5
        },
        {
          "phase": "offset_6_plus",
          "start_offset": 6,
          "duration_years": null,
          "first_follow_up_year": 7
        }
      ],
      "description": "Source-offset profile: displacement, +1, +2–3, +4–5, and +6+; displacement is follow-up year 1, so offset +6 begins in follow-up year 7. Annual baseline rates use a constant-hazard rate-to-risk conversion; odds ratios modify annual risk, and survival compounds across phases. The selected baseline age rate is held fixed over the follow-up horizon."
    },
    "place_application": "initial_only",
    "place_counterfactual": "national child-dollar result is the reference"
  },
  "exposure_provenance": {
    "source": "one-worker normalized reference input",
    "method": "scale by the stored warehouse worker-equivalent exposure at read time"
  },
  "place": null,
  "place_mix": [],
  "input_content_sha256": "65625244b6014b6429cf6d6fd7f3f525fdafb6dce287e996ad1a82b5db273d17",
  "engine_version": "0.4.0",
  "engine_sha256": "99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153",
  "adapter_sha256": "605700852536cef19bdae955f055979ab182f352c107882e7b46fb6cccd3e68e",
  "outcomes": {
    "excess_deaths": {
      "point": 761.3929556467236,
      "low": 298.171209231006,
      "high": 1326.2909102737626,
      "unit": "deaths",
      "baseline": {
        "value": 0.004944,
        "annual_probability": 0.004931798548274205,
        "unit": "deaths_per_person_year",
        "citation": "cdc_wonder D76 (Underlying Cause of Death, 1999-2020), Male 45-54 years, pooled 2015-2019: 514314 deaths / 104024440 person-years = 494.4 per 100k; pulled 2026-09-06 via scraper.cli wonder-mortality into warehouse wonder_mortality",
        "population": "US prime-age men (45-54)",
        "notes": "Pre-pandemic window: excludes 2020 (COVID-distorted; 2020 crude rate 601.5/100k). Single-year 2019 = 490.0/100k. Ages 45-54 match the Sullivan & von Wachter prime-age counterfactual population",
        "sex": "Male",
        "age": "45-54 years",
        "years": "2015-2019",
        "cause": "All causes",
        "geography": "US"
      },
      "steps": [
        {
          "link": "earnings_shock->mortality_peak",
          "phase": "displacement",
          "point": 2.6698,
          "low": 2.1144,
          "high": 3.3711,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offset_1",
          "phase": "offset_1",
          "point": 1.9838,
          "low": 1.3697,
          "high": 2.8732,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offsets_2_3",
          "phase": "offsets_2_3",
          "point": 1.7315,
          "low": 1.3238,
          "high": 2.2649,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offsets_4_5",
          "phase": "offsets_4_5",
          "point": 1.2712,
          "low": 0.97,
          "high": 1.6661,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_sustained",
          "phase": "offset_6_plus",
          "point": 1.1354,
          "low": 1.0335,
          "high": 1.2474,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        }
      ],
      "components": {
        "follow_up_years": 20,
        "method": "odds_survival",
        "timing": "source_profile"
      },
      "applicability": {
        "status": "illustrative_reference_calculation",
        "eligible_for_public_headline": false,
        "target_population": null,
        "decision": null,
        "transport_assumptions": [
          "high-tenure male mass-layoff cohort, ages 45–54",
          "Pennsylvania early-1980s response transported to target place and calendar time",
          "fixed baseline age rate over follow-up; cohort aging is not modeled"
        ],
        "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
      },
      "interpretation": "Conditional modeled expected difference; parameter bands are support envelopes, not a confidence interval.",
      "persistence_sensitivity": {
        "available": true,
        "status": "declared_structural_sensitivity",
        "eligible_for_public_headline": false,
        "unit": "deaths",
        "variants": {
          "source_profile": {
            "point": 761.3929556467236,
            "low": 298.171209231006,
            "high": 1326.2909102737626,
            "evidence_status": "source_profile_with_transport_assumptions",
            "citations": [
              "sullivan2009"
            ]
          },
          "no_sustained_excess": {
            "point": 543.3597360040633,
            "low": 243.32995281508684,
            "high": 936.1966696566208,
            "evidence_status": "structural_assumption",
            "motivating_citations": [
              "eliasonstorrie2009"
            ],
            "assumption": "Retain source odds through offset +5; set offset +6 onward OR=1.",
            "first_changed_follow_up_year": 7,
            "fixed_late_odds_ratio": 1
          }
        },
        "source_minus_no_sustained_point": 218.03321964266038,
        "structural_point_range": {
          "low": 543.3597360040633,
          "high": 761.3929556467236,
          "interpretation": "Range of point estimates across these two assumptions; not a confidence interval or a bound on the true effect."
        },
        "shared_inputs": [
          "exposure",
          "resolved mortality baseline",
          "follow-up horizon",
          "source odds through offset +5"
        ],
        "limitations": [
          "No probabilities or model-average weights are assigned to the structures.",
          "A nonsignificant long-run estimate does not establish an exactly zero effect.",
          "The Swedish study differs in population, design, effect scale and follow-up; this hybrid does not reproduce its estimates or substitute its hazard ratios for odds ratios.",
          "The cutoff follows the source profile's offset +6 phase, not the Swedish study's windows; persistence beyond its 12-year follow-up is an assumption in either direction.",
          "Baseline aging and target-population transport remain unresolved in both structures."
        ]
      }
    },
    "child_lifetime_earnings_lost_usd": {
      "point": 12678813262.779053,
      "low": 3293198250.072483,
      "high": 21405788625.471123,
      "steps": [
        {
          "link": "displacement->child_earnings",
          "kind": "direct",
          "citation": "oreopoulos2008",
          "tier": "EXACT",
          "param_point": 0.9076,
          "param_low": 0.844,
          "param_high": 0.976,
          "value_point": 0.9076,
          "value_low": 0.844,
          "value_high": 0.976,
          "causal_role": "direct_displacement_estimate",
          "population_scope": "Canada 39k father-son pairs firm closures",
          "evidence_role": "conditional"
        }
      ],
      "unit": "usd_2024",
      "baseline": {
        "value": 2591418,
        "unit": "usd_2024",
        "citation": "SSA Annual Statistical Supplement 2025, Table 4.B6 (CWHS/Master Earnings File, 1 percent sample): male median earnings by age, 2023 (preliminary) — synthetic career ages 20-64 = 5x(24218+42561+52485+60423+64962+67506+68160+64854)+2x60666+3x56666 = 2517175 usd_2023; CPI-U annual averages 304.702->313.689 (BLS series CUUR0000SA0, pulled 2026-09-06) -> 2591418 usd_2024; warehouse ssa_median_earnings (pulled via ssa-earnings-download)",
        "population": "US male median lifetime earnings",
        "notes": "Derivation declared: the cross-sectional age profile summed over a 45-year working life (ages 20-64) is a synthetic cohort — the sum of age-band medians approximates rather than equals the median of individual lifetime sums; median-of-workers semantics excludes non-working years; 2023 medians are preliminary (SSA replaces them with final data in a later edition)"
      },
      "applicability": {
        "status": "illustrative_reference_calculation",
        "eligible_for_public_headline": false,
        "target_population": null,
        "decision": null,
        "transport_assumptions": [
          "Canadian father-son firm-closure estimate transported to the target families",
          "US male synthetic career earnings convert a relative adult earnings effect to dollars",
          "lifetime dollars are undiscounted; this is not an annual loss"
        ],
        "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
      },
      "interpretation": "Conditional modeled expected difference; parameter bands are support envelopes, not a confidence interval."
    }
  }
}

Parameter set v1.52 · model v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1

Local connections

County context, public notices, and linked public records.

Community well-being

Food insecurity, SNAP receipt, mental distress, smoking, and overdose mortality in this area. CDC models these from survey data: treat them as local estimates, not headcounts. Bars compare each estimate against population-weighted averages of all reporting areas for the same data year.

Food insecurity

2023

8.4%: 6.8 points below U.S.

Households on SNAP

2023

5.6%: 6.3 points below U.S.

Frequent mental distress

2023

15.1%: 0.9 points below U.S.

Adult smoking

2023

12.2%: 0.1 points above U.S.

Drug overdose deaths

2021

33.6: 1.5 above U.S.

Source: CDC PLACES 2025 release (BRFSS survey year 2023) and NCHS drug poisoning mortality. PLACES values are model-based small-area estimates, not survey counts. Benchmarks are population-weighted averages across all reporting areas.

Medical workforce context

AHRF supply DOL filingsRecordAHRF county supply data and H-1B medical LCAs. Comparisons use the median US county.
MDs per 100k residents106↑ 41% above
Active MDs (non-federal)440
Nurse practitioners per 100k101↑ 5% above
County population416,659
Primary care HPSA designationsnot a designated shortage area0
H-1B medical workers certifiedhealthcare SOCs (29-* + 31-2*)13670% of BLS
Full medical breakdown

St. Charles County in context

DOL filings CountyRecordH-1B intensity by county across Missouri. This county is highlighted. Click any county to drill in.
Loading map…
Read the county map County-level H-1B intensity

The map gives geographic context. A county average does not classify every filing, employer, or worker within it.

Employers & occupations

The sponsors and job categories recorded in this county.

Employers (1,800)

DOL filings EmployerRecordRanked by applications in this county.
EmployerFilings
1

Mastercard International Incorporated

1,789
2

Wipro Limited ⚠ Dep

1,049
3

Tech Mahindra (AMERICAS), Inc. ⚠ Dep

846
4

Mastercard Technologies, LLC

735
5

Tata Consultancy Services Limited ⚠ Dep

269
6

Inspirix Technologies LLC ⚠ Dep

153
7

Satyam Computer Services Ltd. ⚠ Dep

152
8

Cognizant Technology Solutions US Corp. ⚠ Dep

141

Job categories (109)

  • Software Developers$60.2M · 57.7%
  • Computer and Information Systems Managers$10.1M · 9.7%
  • Management Analysts$9.8M · 9.4%
  • Computer Occupations, All Other$8M · 7.7%
  • Computer Programmers$6.3M · 6.0%
  • Software Quality Assurance Analysts and Testers$4M · 3.8%
  • Computer Systems Analysts$3.6M · 3.5%
  • Data Scientists$2.1M · 2.1%
DOL wage offers BLS occupationsSignalOccupation averages need not describe each filing.
Job categoryH-1B vs BLS
15-1252 Software DevelopersH-1B $112K vs BLS $136K-18%

2,219 workers · 2,191 filings · $60.2M wage theft

195 workers · 151 filings · $10.1M wage theft

13-1111 Management AnalystsH-1B $80.1K vs BLS $101.9K-21%

389 workers · 163 filings · $9.8M wage theft

15-1299 Computer Occupations, All OtherH-1B $100.2K vs BLS $116.6K-14%

353 workers · 252 filings · $8.0M wage theft

15-1251 Computer ProgrammersH-1B $81.2K vs BLS $100.4K-19%

239 workers · 120 filings · $6.3M wage theft

143 workers · 112 filings · $4.0M wage theft

15-1211 Computer Systems AnalystsH-1B $93.3K vs BLS $105.9K-12%

200 workers · 113 filings · $3.6M wage theft

15-2051 Data ScientistsH-1B $104.8K vs BLS $120.2K-13%

97 workers · 97 filings · $2.1M wage theft

Labor condition applications (11,833)

DOL filings BLS occupationsRecordAll recorded outcomes and visa classes. Use the wage badge to inspect an offer against available benchmarks.
Title · Worksite

A negative % sits below the BLS market median; a positive % sits above.

What the filing rows show One application per row

Each row links to the disclosure record. A wage comparison is a screening calculation, not a finding of a wage violation.

WARN notices (3)Public layoff notices: open to inspect
WARN EmployerReviewOpen a notice to inspect its stated effective date and worker count. Coverage varies by state; some states file no public WARN data.

Nike IHM, Inc (dba AirMI)

2026-06-26 · St. Charles

--

General Mills Operations, LLC

2026-06-08 · St. Charles

--

LarKen Logistics LLC

Notice date: 2025-09-03 · St. Peters

--

Records to inspect

Open the linked public records behind this county's filings.

Immigration law firms (504)

DOL filings Law firmRecordNames are shown as recorded.

Federal contracts (2,712)

Federal awards EmployerRecordAmounts are individual award actions, not total contract values.
MADIAN IT SOLUTIONS LLC
Department of Defense · Feb 12, 2026
$9.3M
MADIAN IT SOLUTIONS LLC
Department of Defense · Nov 20, 2025
$4.2M
MADIAN IT SOLUTIONS LLC
Department of Defense · Jan 8, 2026
$3.4M
MIDWEST WEATHER INC
Department of Transportation · Jul 6, 2026
$2.8M
STAUDER CONSULTING, INC.
Department of Defense · Dec 23, 2025
$2.8M
MIDWEST WEATHER INC
Department of Transportation · Dec 3, 2025
$2.4M
MIDWEST WEATHER INC
Department of Transportation · Mar 24, 2026
$1.8M
MADIAN IT SOLUTIONS LLC
Department of Defense · Jun 2, 2026
$1.6M

Evidence & sources

Scope, methods, and source coverage for this county record.

Public source records and site analysis. We do not attest to accuracy. Read the full disclaimer.

Dataset guides and site methods

  1. [1] Dataset documentation · DOL OFLC. LCA public disclosure record layout (FY2026 Q3). Pages 1–4: application, DOL outcome and dates, requested positions, employer, representatives, worksites and pay unitsThis layout covers determinations issued October 1, 2025 through June 30, 2026. It documents employer-provided application fields and DOL decisions, not USCIS decisions, payroll verification, legal bills or worker-linked moves. Older layouts can differ.Checked 2026-10-17.
  2. [2] Dataset documentation · BLS. OEWS technical notes (May 2025). Scope of the survey; occupational coding; concepts and estimation methodologyDocuments occupation and geographic wage estimates, not an individual worker’s pay. Use the estimate year and geography stated by the site; older releases can differ.Checked 2026-10-17.
  3. [3] XH1B method or registry · XH1B. WARN Notices (mass layoffs): source registry; Calculation and Matching Methods; Reading Public Records and Derived Indicators. Source registry entry: warn; Filing units, annualization, weighting, wage comparisons, and inference limits; Reading records: units, source coverage, wage gaps, entity links, and inference limitsXH1B dataset description: One row per source_notice_id. The definition of a mass layoff and the layoff threshold vary by state. The threshold is typically 50 or more employees.; These are the site's review methods, not validated predictions of wrongdoing. Inspect underlying records and alternative explanations.
  4. [4] Dataset documentation · USAspending / U.S. Treasury. Federal Spending Guide: contract transactions. Pages 3, 5, 9 and 17: transactions, amount fields and recipient identifiersContract downloads contain prime award transactions. XH1B’s use of recipient identifiers for employer links is its own processing step.Checked 2026-10-18.
  5. [5] XH1B method or registry · XH1B. Displacement Model and Assumptions. Eligibility, requested-position weighting, scopes, WARN matching, and counting limitsModel outputs are estimates. A matched layoff notice does not prove that an H-1B worker replaced a laid-off worker.
  6. [6] XH1B method or registry · XH1B. Downstream Research and Methods. Study populations, parameter bounds, baselines, and expected outcomes; linked model card
  7. [7] Dataset documentation · HRSA. Area Health Resources Files: 2024–2025 technical documentation. County User Guide: physicians, Table 10 NPI professions, population estimates and missing values; Technical Documentation: variable years and sourcesClinician categories and variable years differ. County APRN counts use NPI taxonomy; physician active and federal status matter. Release year is not the year of every measure.Checked 2026-10-18.
Questions about the data & methods

How many H-1B filings are in St. Charles County, MO?

11,445 H-1B labor condition applications requesting 21,038 workers have been filed in St. Charles County, MO, per Department of Labor disclosure records.

How many employers have H-1B filings in St. Charles County, MO?

1,781 distinct employers have filed H-1B labor condition applications in St. Charles County, MO. The employer list on this page is ranked by filings and wage impact.

What worker-equivalent exposure does the displacement model estimate for St. Charles County, MO?

The model estimates 26,475 worker-equivalents of displacement exposure in St. Charles County, MO: one per requested worker on a certified H-1B filing, raised where the offered wage sits below the occupation's BLS median, plus government-reported WARN layoffs matched to filings. This is a modeled exposure estimate, not a count of documented job losses; the formula is on the About page.

What is the median H-1B wage in St. Charles County, MO?

$85,925 per year is the median wage offered on H-1B labor condition applications filed for work in St. Charles County, MO. The wage-distribution chart on this page shows the spread around that median.

Who files the most H-1B filings in St. Charles County, MO?

Mastercard International Incorporated leads with 1,789 filings, about 16% of all St. Charles County, MO filings. Its dossier page carries the full filing, wage, and layoff history.

What share of St. Charles County, MO H-1B filings does DOL deny?

DOL disclosure records show 11,227 certified, 72 denied, 256 withdrawn of 11,555 labor condition applications with reported outcomes in St. Charles County, MO. The denial share is 1% across the reported outcomes.

How many WARN layoff notices has St. Charles County, MO recorded?

3 Worker Adjustment and Retraining Notification (WARN) notices. Where a layoff employer then filed H-1B labor condition applications in the same window, the pair is recorded as a displacement event with an evidence score.

When did H-1B use peak in St. Charles County, MO?

Filings peaked in 2019 at 1,158 labor condition applications. The filings-by-year chart on this page shows the full trend since records began.

Which immigration law firms file the most H-1B filings in St. Charles County, MO?

504 distinct law firms and agents have filed H-1B applications for employers in St. Charles County, MO. The law-firm table on this page ranks them by filings and by the wage gap their filings carry.

Do St. Charles County, MO H-1B employers hold federal contracts?

2,712 federal contract actions in St. Charles County, MO name employers that also file H-1B labor condition applications. The contracts table links each award to the employer dossier. A shared employer name does not show how award funds were spent.

Where does the St. Charles County, MO H-1B data come from?

Every figure on this page traces to a public government record: DOL OFLC disclosure files (LCA filings, wages, outcomes), BLS OES wage data (occupation medians), state WARN notices, and federal contract awards. The archive is read-only evidence; nothing is crowdsourced or anonymous.