Python Data Analysis Salary
$27.5K - $41.5K
1% of jobs
$41.5K - $55.5K
0% of jobs
$55.5K - $69.5K
3% of jobs
$69.5K - $83.5K
5% of jobs
$83.5K - $97.5K
12% of jobs
$100.9K is the 25th percentile. Wages below this are outliers.
$97.5K - $111.5K
17% of jobs
The median wage is $118.6K / yr.
$111.5K - $125.5K
24% of jobs
$136.4K is the 75th percentile. Wages above this are outliers.
$125.5K - $139.5K
17% of jobs
$139.5K - $153.5K
12% of jobs
$153.5K - $167.5K
6% of jobs
$167.5K - $181.5K
3% of jobs
$27.5K
$119K
$180K
$121,932
/year
$58.62
/hour
Python Data Analysis Salary Comparison by Location
Nationwide
United States
$121,932
Columbus
Ohio
$117,774
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How much does a Python Data Analysis make?
As of Jun 3, 2026, the average annual pay for a Python Data Analysis in the United States is $121,932 a year.
Just in case you need a simple salary calculator, that works out to be approximately $58.62 an hour. This is the equivalent of $2,344/week or $10,161/month.
While ZipRecruiter is seeing annual salaries as high as $180,000 and as low as $27,500, the majority of Python Data Analysis salaries currently range between $100,500 (25th percentile) to $138,500 (75th percentile) with top earners (90th percentile) making $160,000 annually across the United States. The average pay range for a Python Data Analysis varies greatly (by as much as 38000), which suggests there may be many opportunities for advancement and increased pay based on skill level, location and years of experience.
A Python Data Analysis in your area makes on average $117,774 per year, or $4,158 (3.410%) less than the national average annual salary of $121,932. Ohio ranks number 31 out of 50 states nationwide for Python Data Analysis salaries.
To estimate the most accurate annual salary range for Python Data Analysis jobs, ZipRecruiter continuously scans its database of millions of active jobs published locally throughout America.
Find your next high paying job as a Python Data Analysis on ZipRecruiter today.
What are Top 10 Highest Paying Cities for Python Data Analysis Jobs
We've identified 10 cities where the typical salary for a Python Data Analysis job is above the national average. Topping the list is Cupertino, CA, , with Sitka, AK, and Wyoming, WY, close behind in the second and third positions. Wyoming, WY, beats the national average by $23,488 (19.3%), and Cupertino, CA, furthers that trend with another $28,501 (23.4%) above the $121,932 average.
With these 10 cities having average salaries higher than the national average, the opportunities for economic advancement by changing locations as a Python Data Analysis appears to be exceedingly fruitful.
Finally, another factor to consider is the average salary for these top 10 cities varies very little at 5% between Cupertino, CA, and Danville, CA, , reinforcing the limited potential for much wage advancement. The possibility of a lower cost of living may be the best factor to use when considering location and salary for a Python Data Analysis role.
City | Annual Salary | Hourly Wage |
|---|---|---|
Cupertino, CA | $150,433 | $72.32 |
Sitka, AK | $146,890 | $70.62 |
Wyoming, WY | $145,420 | $69.91 |
Santa Clara, CA | $144,000 | $69.23 |
Mountain View, CA | $143,841 | $69.15 |
San Francisco, CA | $143,658 | $69.07 |
Sunnyvale, CA | $143,106 | $68.80 |
Livermore, CA | $143,025 | $68.76 |
San Jose, CA | $142,871 | $68.69 |
Danville, CA | $142,661 | $68.59 |
What are Top 5 Best Paying Related Python Data Analysis Jobs in the U.S.
Analyzing some similar jobs related to the Python Data Analysis job category, we found that Ontology Engineer jobs have average salaries similar than Python Data Analysis jobs.
Job Title | Annual Salary | Hourly Wage |
|---|---|---|
Ontology Engineer | $107,282 | $51.58 |
Analytics Implementation Engineer | $106,928 | $51.41 |
Data Analyst Programmer | $94,931 | $45.64 |
Power Bi Data Analyst | $82,640 | $39.73 |
Associate Data Engineer | $38,974 | $18.74 |
About Our Data
ZipRecruiter salary estimates, histograms, trends and comparisons are derived from both employer job postings and third party data sources.
