Pitney Bowes Inc. salaries
Median $141,200 across 36 filings for IT roles, Jul 2023 to Jun 2026.
Calculate take-home pay on the calculator pageMedian
$141,200
Middle 50%
$119,100–$167,800
Filings
36
- Median is 10% above the median for all IT roles ($128,000).
- Most filings are wage Level IV (61%).
- Software Developers has the most filings (16), with a median of $146,200.
Salaries by role
| Role | Filings | Median |
|---|---|---|
| Software Developers | 16 | $146,200 |
| Computer Systems Analysts | 6 | $154,700 |
| Data Scientists | 5 | $115,000 |
| Software Quality Assurance Analysts and Testers | 4 | $139,300 |
| Computer Occupations, All Other | 2 | $181,200 |
| Database Administrators | 2 | $138,100 |
| Information Security Analysts | 1 | $104,000 |
Top metros
| Metro | Filings | Median |
|---|---|---|
| Austin-Round Rock-San Marcos, TX | 4 | $169,300 |
| Dallas-Fort Worth-Arlington, TX | 4 | $148,600 |
| Waterbury-Shelton, CT | 4 | $140,000 |
| Omaha, NE-IA | 3 | $141,000 |
| Albany-Schenectady-Troy, NY | 1 | $139,200 |
| Ann Arbor, MI | 1 | $90,200 |
| Boston-Cambridge-Newton, MA-NH | 1 | $140,000 |
| Charlotte-Concord-Gastonia, NC-SC | 1 | $147,200 |
| Chicago-Naperville-Elgin, IL-IN | 1 | $167,300 |
| Durham-Chapel Hill, NC | 1 | $99,800 |
Level II 25%
Level III 14%
Level IV 61%
Take-home pay
| Gross | $141,200 |
| Federal income tax | $22,600 |
| Social Security | $8,800 |
| Medicare | $2,000 |
| State income tax | $0 |
| Health insurance (employee share) | $1,400 |
| Take-home per year | $106,300 |
| Take-home per month | $8,900 |
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.