ICF Resources, LLC salaries
Median $91,800 across 22 filings for IT roles, Jul 2023 to Jun 2026.
Calculate take-home pay on the calculator pageMedian
$91,800
Middle 50%
$80,200–$126,100
Filings
22
- Median is 28% below the median for all IT roles ($128,000).
- Most filings are wage Level I (50%).
- Data Scientists has the most filings (14), with a median of $86,400.
Based on 22 filings. Small samples can differ from actual pay ranges.
Salaries by role
| Role | Filings | Median |
|---|---|---|
| Data Scientists | 14 | $86,400 |
| Database Administrators | 3 | $126,500 |
| Computer Occupations, All Other | 2 | $143,600 |
| Software Developers | 2 | $139,400 |
| Computer Systems Analysts | 1 | $125,000 |
Top metros
| Metro | Filings | Median |
|---|---|---|
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 4 | $131,500 |
| Oklahoma City, OK | 3 | $75,400 |
| Albany-Schenectady-Troy, NY | 2 | $70,000 |
| New York-Newark-Jersey City, NY-NJ | 2 | $93,700 |
| Austin-Round Rock-San Marcos, TX | 1 | $90,000 |
| Baltimore-Columbia-Towson, MD | 1 | $84,300 |
| Chicago-Naperville-Elgin, IL-IN | 1 | $90,000 |
| Dallas-Fort Worth-Arlington, TX | 1 | $130,000 |
| Denver-Aurora-Centennial, CO | 1 | $126,500 |
| Killeen-Temple, TX | 1 | $93,600 |
Level I 50%
Level II 5%
Level III 5%
Level IV 5%
Not stated 36%
Take-home pay
| Gross | $91,800 |
| Federal income tax | $11,400 |
| Social Security | $5,700 |
| Medicare | $1,300 |
| State income tax | $4,800 |
| Health insurance (employee share) | $1,400 |
| Take-home per year | $67,100 |
| Take-home per month | $5,600 |
Tax year 2026, single filer.
Local taxes, 401(k), and filing status other than single are not included.
Tax rates checked against IRS, Tax Foundation, and other original sources on Oct 28, 2026.
This is an estimate. Actual taxes depend on your situation. Consult a tax professional before filing.
LCA filings are not hires.
Filed wages are offered base pay, not total compensation.
We did not independently verify the source files. Deduplication and filtering can cause differences from the original data.