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Data Scientists Salary: Minnesota vs California

Data Scientists earn a median of $128,800 in Minnesota and $141,590 in California. That is a nominal gap of $12,790 (-9.0%), with California paying more before any cost-of-living adjustment.

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics survey, May 2025 estimates. Cost-of-living adjustment uses BEA Regional Price Parities, most recent release.

$128,800
Minnesota median
$130,601 after COL
$141,590
California median
$127,881 after COL
-9.0%
Nominal gap
California leads
+2.1%
Adjusted gap
Minnesota leads after COL

The story behind the numbers

On raw wages, California pays $12,790 more per year than Minnesota for data scientists, a gap of +9.0%.

After adjusting for cost of living, the picture flips. Minnesota actually offers more purchasing power, effectively paying $2,720 more in national-price-level terms (a +2.1% real gap). The higher nominal wage in the other location is eaten up by higher local prices.

Full breakdown by location

Detailed wage, employment, and cost-of-living figures for data scientists in each location. Click through to the full local salary page for percentiles, outlook, and peer areas.

Data Scientists

Minnesota

Median salary
$128,800
Mean salary
$126,290
Employment
4,020
Location quotient
0.81
Jobs per 1,000
1.4
COL-adjusted median
$130,601
Regional Price Parity
98.6%

Exact state RPP match.

Full Data Scientists page for Minnesota →

Data Scientists

California

Median salary
$141,590
Mean salary
$156,000
Employment
39,310
Location quotient
1.28
Jobs per 1,000
2.2
COL-adjusted median
$127,881
Regional Price Parity
110.7%

Exact state RPP match.

Full Data Scientists page for California →

Related pages

Keep digging into data scientists from a different angle.

Common questions about this comparison

What does the cost-of-living adjustment actually do? +

It divides each location's nominal median wage by its Regional Price Parity (RPP), which measures how local prices compare to the national average (100 = national). A wage of $100,000 in an area with RPP 120 has the same purchasing power as roughly $83,000 nationally.

Why would the nominal and adjusted winners disagree? +

High-cost metros often pay higher salaries, but not by enough to fully offset the higher cost of housing, goods, and services. When that happens, the location with the lower nominal wage actually offers more real purchasing power.

What is a location quotient? +

The location quotient measures how concentrated an occupation is in a given area versus the national average. A value of 2.0 means the occupation is twice as common there as nationally. It is a signal of what a state specializes in.