$167,500
median · per year, annualized USD
$163,800
median · per year, annualized USD
Data Scientist, SMB Ads Growth
Data Scientist, Cybersecurity
Data Scientist, Ads Demand
Data Scientist, FinEng
Data Scientist, B2B Strategy & Intelligence
Staff Data Scientist - Growth & Marketing ($400k - $500k)
Senior / Staff Data Scientist, Applied AI
Research Scientist - Environments, Data and Post-Training
Data Scientist
Machine Learning Research Engineer/Scientist
Staff Machine Learning Operations Engineer
Machine Learning Engineer/Senior Machine Learning Engineer - Devops, AI for Drug Discovery
Principal Machine Learning Operations Engineer
Lead ML Engineer - Advance AI (applied ML, LLM's, ML Ops)
Senior / Staff ML Ops Engineer
Lead Software Platform Engineer, MLOps
Software Engineer - ML Ops (R37)
Staff MLOps Engineer
Senior Staff ML Ops Engineer
Matterport - Senior ML Ops Engineer
| Company | Median | Roles |
|---|---|---|
Booz Allen Hamilton
|
$126,800 | 113 |
Leidos
|
$151,475 | 21 |
OpenAI
|
$332,250 | 16 |
Accenture Federal Services
|
$166,850 | 16 |
Roche
|
$228,700 | 15 |
| GR GRVTY | $137,500 | 15 |
RELX
|
$133,100 | 15 |
Faire
|
$250,750 | 14 |
| Company | Median | Roles |
|---|---|---|
Weekday AI
|
$202,800 | 2 |
Target
|
$197,000 | 2 |
Workday
|
$150,400 | 2 |
RELX
|
$140,450 | 2 |
Booz Allen Hamilton
|
$126,300 | 2 |
Shirley Ryan AbilityLab
|
$88,225 | 2 |
Garner Health
|
$324,500 | 1 |
AiDASH, Inc.
|
$250,000 | 1 |
| Location | Median | Roles |
|---|---|---|
| San Francisco | $220,000 | 215 |
| Seattle | $207,588 | 66 |
| New York | $198,000 | 197 |
| Singapore | $187,200 | 3 |
| Boston | $172,450 | 42 |
| Denver | $167,950 | 13 |
| Austin | $165,500 | 21 |
| Los Angeles | $157,500 | 30 |
| Chicago | $150,000 | 47 |
| Atlanta | $142,610 | 16 |
The median for Data Scientist is $167,500 per year (typically $130,500–$214,314), versus $163,800 for MLOps ($137,000–$193,500). That puts Data Scientist about 2% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so Data Scientist and MLOps are compared on equal terms regardless of the currency each role was originally posted in. Only roles that publish a salary range feed the medians; numbers refresh every few hours as new roles post and older ones close, so this comparison reflects the market right now rather than a fixed survey. Use it as a directional benchmark when weighing one path against the other.