Side-by-side compensation comparison across national and state-level data.
Data Scientists out-earn Data Analysts by $48,300 (31%) on median.
Percentiles for 2026. Higher percentile values reflect senior/specialized roles.
| Percentile | Data Analyst | Data Scientist | Difference |
|---|---|---|---|
| 25th | $75,600 | $117,700 | $42,100 |
| Median (50th) | $107,200 | $155,500 | $48,300 |
| 75th | $140,800 | $201,700 | $60,900 |
| 90th (top earners) | $176,500 | $252,100 | $75,600 |
Which job wins in each state (based on median annual salary).
| State | Data Analyst | Data Scientist | Higher Pay |
|---|---|---|---|
| California | $150,000 | $241,000 | Data Scientist |
| Texas | $115,700 | $167,900 | Data Scientist |
| Florida | $109,300 | $158,600 | Data Scientist |
| New York | $139,300 | $209,900 | Data Scientist |
| Pennsylvania | $111,500 | $161,700 | Data Scientist |
| Illinois | $116,800 | $169,500 | Data Scientist |
| Ohio | $99,700 | $144,600 | Data Scientist |
| Georgia | $110,400 | $160,200 | Data Scientist |
| North Carolina | $106,100 | $153,900 | Data Scientist |
| Michigan | $102,900 | $149,300 | Data Scientist |
| New Jersey | $135,000 | $195,900 | Data Scientist |
| Virginia | $121,100 | $175,700 | Data Scientist |
| Washington | $144,700 | $220,800 | Data Scientist |
| Arizona | $108,200 | $157,000 | Data Scientist |
| Massachusetts | $139,300 | $202,100 | Data Scientist |
Builds statistical models and ML pipelines for product and business decisions.
Nationally, Data Scientists out-earn Data Analysts by approximately $48,300 per year (31% difference). However, this varies by state, experience level, and specific employer.
Both fields have positive 2026 growth outlooks. Data Analysts are projected at +2.5% YoY wage growth, while Data Scientists are at +2.5%. Beyond wage growth, consider opportunity density (job openings) and your geographic flexibility.
Data Analyst typically requires: Transforms raw data into business insights using SQL, Excel, BI tools.. Data Scientist typically requires: Builds statistical models and ML pipelines for product and business decisions.. Compare the formal requirements against your existing skills and education to assess the switching cost.
Salary is one input among many. Job satisfaction, skills transferability, geographic fit, and long-term ceiling matter as much as median pay. Use this as a benchmark, then dig into job descriptions and talk to people in both fields before deciding.