Data Scientists: Washington vs West Virginia pay

Percentile	Published wages	Washington	West Virginia
10th	Washington$79,930West Virginia$57,500	$79,930	$57,500
25th	Washington$105,240West Virginia$69,790	$105,240	$69,790
Median	Washington

Place	Employment	Jobs per 1,000	Location quotient	Employment RSE
Washington	9,600Jobs per 1,000: 2.71 Location quotient: 1.6	2.71	1.6	3.4%
West Virginia	390Jobs per 1,000: 0.55 Location quotient: 0.33	0.55	0.33	22%

75th	Washington$208,320West Virginia$112,770	$208,320	$112,770

90th	Washington$220,040West Virginia$125,100	$220,040	$125,100

Start with the answer

Data Scientists pay in Washington and West Virginia

The May 2025 BLS OEWS median for Data Scientists is $163,350 per year in Washington. It is $85,090 per year in West Virginia. Washington is 92.0% above West Virginia on the published median.

Both rows use SOC 15-2051 and the same annual wage metric. Median means the middle of each area's published wage spread. It is not one worker's pay. The larger median is not proof that one place gives a better job or a better result. It is one wage fact from one source period.

BLS lists 9,600 wage and salary jobs in Washington and 390 in West Virginia. Those are survey job counts, not open posts. Read pay, job scale, local share, and price level as separate facts before you make a choice.

Evidence: bls-oews-may-2025 · Rule: same-soc-same-metric-pair · nominal-median-gap · employment-not-openings

Pay range

Compare the full Data Scientists wage ladder

A median can hide a wide range. The 10th, 25th, 50th, 75th, and 90th percentile points show more of each area's spread. A percentile is a rank point. It is not a career stage. The 10th point does not mean new-worker pay. The 90th point does not mean a wage that comes after a set number of years.

The lower half can differ from the upper half. One area can lead at the median and trail at another point. Read each field against the same field in the other area. Do not compare one area's 75th percentile with the other area's median. That would answer a different question.

A posted job range can sit below, across, or above these marks. That does not make the post wrong. A listing can differ by employer, level, hours, field, or work rules. Keep the listing tied to that employer. Keep the BLS range tied to the whole role-place row.

10th percentile: Washington is $79,930 per year; West Virginia is $57,500 per year. Washington is 39.0% above West Virginia at this point.
25th percentile: Washington is $105,240 per year; West Virginia is $69,790 per year. Washington is 50.8% above West Virginia at this point.
Median: Washington is $163,350 per year; West Virginia is $85,090 per year. Washington is 92.0% above West Virginia at this point.
75th percentile: Washington is $208,320 per year; West Virginia is $112,770 per year. Washington is 84.7% above West Virginia at this point.
90th percentile: Washington is $220,040 per year; West Virginia is $125,100 per year. Washington is 75.9% above West Virginia at this point.

Evidence: bls-oews-may-2025 · Rule: paired-percentile-fields · same-field-comparison · posted-pay-separation

Shape of pay

Mean and median tell two parts of the Data Scientists story

Washington has a mean of $158,040 per year and a median of $163,350. West Virginia has a mean of $90,730 per year and a median of $85,090. Mean adds all wage values and splits the total by the number of jobs behind the estimate.

Washington's mean is 3.3% below its median on the same published median. West Virginia's mean is 6.6% above its median on the same published median. The gaps show that each wage spread has a shape. They do not explain why the shape differs.

Use median for the middle. Use mean to see how the full set pulls. Use percentiles to see more of the spread. None of the three is a pay promise. A person, team, or listing can sit far from all three for reasons that are outside these BLS rows.

Evidence: bls-oews-may-2025 · Rule: paired-mean-median · mean-median-gap · no-causal-inference

Job scale

How the two Data Scientists job bases differ

Washington has 9,600 estimated Data Scientists jobs. West Virginia has 390. The larger count shows a larger covered job base in this source. It does not show more open roles, faster hiring, or a better chance for one applicant.

Washington has 2.71 Data Scientists jobs per 1,000 local jobs. West Virginia has 0.55 per 1,000. This rate helps compare places of different size. It is not a job-post rate and does not use the MeritLog catalog.

The employment RSE is 3.4% in Washington and 22% in West Virginia. RSE means relative standard error. It is a survey precision flag. It is not the chance that the job count or one person's pay is right.

Evidence: bls-oews-may-2025 · Rule: paired-employment · paired-jobs-per-thousand · employment-rse-field-scope

Local share

Where Data Scientists takes a larger share of jobs

The location quotient is 1.6 in Washington and 0.33 in West Virginia. A value of 1 means the role has the same share of local jobs as it has across the nation. A value above 1 means the local share is larger. A value below 1 means it is smaller.

Washington's quotient is 384.8% above West Virginia's. That gap is about the job mix. It is not a wage gap, a job-count gap, or a growth claim.

Read location quotient with employment. A small place can have a high share and few jobs. A large place can have many jobs and a share near the national mark. Then read pay as its own field. The three measures do not form one score.

Evidence: bls-oews-may-2025 · Rule: paired-location-quotient · quotient-gap · metric-separation

BEA price view

How price levels differ between Washington and West Virginia

BEA's 2024 all-items price index is 107.0 in Washington and 89.5 in West Virginia. The U.S. level is 100. A higher number means the broad local price level is higher than the national mark. It does not say a place is good or bad.

Housing is 126.0 in Washington and 54.2 in West Virginia. Goods are 104.4 and 96.5. Utilities are 92.9 and 92.2. Other services are 103.9 and 99.9. The parts can move in different ways.

The wage period is May 2025. The price period is 2024. WageScope keeps those clocks visible. It uses the all-items index for one clear proxy. It does not mix BEA prices into the BLS source row, and it does not claim the two releases describe the exact same month.

Evidence: bea-rpp-2024 · bls-oews-may-2025 · Rule: paired-rpp-fields · rpp-us-baseline · source-period-separation

Price-level proxy

Compare the medians in national-price dollars

WageScope divides Washington's $163,350 median by 107.0 divided by 100. The result is $152,645 per year. It divides West Virginia's $85,090 median by 89.5 divided by 100. That result is $95,076 per year.

Washington's proxy is 60.6% above West Virginia's. The nominal gap is 92.0%. The order can stay the same or change after the price-level step. Both results must keep their labels.

The proxy is a narrow math tool. It is not take-home pay. It does not add taxes, benefits, household size, debt, commute, schools, safety, climate, or taste. It does not set a wage target. Use it to see how one broad price index changes the wage view, then check your own costs outside WageScope.

Evidence: bls-oews-may-2025 · bea-rpp-2024 · meritlog-bounded-comparison-v1 · Rule: price-level-adjusted-formula · nominal-adjusted-gap-separation · proxy-limits

Same-proxy pay

What equal price-level pay would look like in the other place

$163,350 per year in Washington has the same national-price-dollar proxy as $136,613 per year in West Virginia. The math keeps Washington's proxy fixed, then applies West Virginia's all-items price index.

$85,090 per year in West Virginia has the same proxy as $101,743 per year in Washington. This reverse view is useful because the answer depends on which wage you start with. It is not a claim about an offer in either place.

Equivalent nominal pay uses one broad price measure. It does not know what a person buys. It does not know rent, family size, debt, taxes, travel, benefits, or savings. Treat the result as a clean source-backed comparison, not a full move plan or a number an employer must match.

Evidence: bls-oews-may-2025 · bea-rpp-2024 · meritlog-bounded-comparison-v1 · Rule: equivalent-nominal-value-forward · equivalent-nominal-value-reverse · proxy-limits

Data care

Check the survey marks before you use the gap

The mean-wage RSE is 2% in Washington and 3.3% in West Virginia. The employment RSE is 3.4% and 22%. RSE is a precision flag for the field it sits beside. It is not a score for the whole page.

BLS does not publish the same RSE field for the median and each percentile. WageScope does not move a mean RSE to the median. It does not use an employment RSE as a wage care mark. Each value stays tied to its source field. Missing or top-coded values also keep their source state.

A later BLS or BEA release can change the result. MeritLog checks the official source clocks before promotion. The page cannot call its data current when a newer complete release is waiting for review. Current job cards have their own seen date and do not make the government data newer.

Evidence: bls-oews-may-2025 · Rule: paired-rse-field-scope · no-rse-transfer · independent-source-freshness

Use the result

A short check list for Washington and West Virginia

Start with the same Data Scientists wage field. Then read the full percentile spread. Check job count, jobs per 1,000, and location quotient. Add the 2024 all-items and housing price levels. Read the national-price-dollar proxy with its limits. Keep the BLS and BEA dates in view.

Next, inspect one current employer-title match in each place when an exact public place match exists. A job post can show work level, hours, location rules, and pay that the BLS row cannot. The post is dated employer evidence. It does not change the survey median or prove a broad trend.

Last, use your own facts. Compare the job needs with work you have done and can support. A wage gap cannot show fit. A price-level gap cannot show fit. A job count cannot show fit. MeritLog's résumé path starts only after you choose a listing and confirm the work facts you want to use.

Evidence: bls-oews-may-2025 · bea-rpp-2024 · meritlog-public-job-boundary-v1 · Rule: comparison-checklist · job-source-separation · confirmed-resume-evidence

Limits

What this Data Scientists comparison does not decide

The page does not choose Washington or West Virginia for you. It does not say what one worker earns. It does not promise a job, offer, raise, or move result. It does not say why the medians differ. It does not turn the larger wage, job count, quotient, or proxy into a place score.

The comparison leaves out people who work for themselves and other work outside the OEWS scope. It does not add taxes, take-home pay, benefits, stock, bonus pay, hours, travel, remote work, or a household budget. Current listings are separate and can be empty even when the government rows are complete.

Use this page for a bounded choice. Compare the same May 2025 BLS role and metric across two exact areas. Add the separate 2024 BEA price view. Inspect dated employer-title matches. Then build a résumé from facts you have confirmed. Keep each source tied to the question it can answer.

Evidence: bls-oews-may-2025 · bea-rpp-2024 · meritlog-public-job-boundary-v1 · Rule: no-place-choice · no-personal-pay-claim · source-purpose-separation

Data Scientists: Washington vs West Virginia

Same occupation, same annual wage metric

The winner can change when local prices differ

Housing and all-items indexes explain the adjustment

Equivalent nominal pay, using price levels only

Employment scale and local concentration

Compare another occupation or pair

Data Scientists: Washington and West Virginia guide

Data Scientists in Washington and West Virginia: common questions

Compare Data Scientists listings by place

Washington

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West Virginia

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Current jobs

Tailor for a real Data Scientists job, not a generic wage number.

Data Scientists pay in Washington and West Virginia

Compare the full Data Scientists wage ladder

Mean and median tell two parts of the Data Scientists story

How the two Data Scientists job bases differ

Where Data Scientists takes a larger share of jobs

How price levels differ between Washington and West Virginia

Compare the medians in national-price dollars

What equal price-level pay would look like in the other place

Check the survey marks before you use the gap

A short check list for Washington and West Virginia

What this Data Scientists comparison does not decide

Compare Data Scientists listings by place

Washington

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West Virginia

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Privacy choices

Data Scientists: Washington vs West Virginia

Same occupation, same annual wage metric

The winner can change when local prices differ

Housing and all-items indexes explain the adjustment

Equivalent nominal pay, using price levels only

Employment scale and local concentration

Compare another occupation or pair

Data Scientists: Washington and West Virginia guide

Data Scientists in Washington and West Virginia: common questions

Compare Data Scientists listings by place

Washington

Exact location filter unavailable.

West Virginia

We could not load these listings.

Current jobs

Tailor for a real Data Scientists job, not a generic wage number.

Data Scientists pay in Washington and West Virginia

Compare the full Data Scientists wage ladder

Mean and median tell two parts of the Data Scientists story

How the two Data Scientists job bases differ

Where Data Scientists takes a larger share of jobs

How price levels differ between Washington and West Virginia

Compare the medians in national-price dollars

What equal price-level pay would look like in the other place

Check the survey marks before you use the gap

A short check list for Washington and West Virginia

What this Data Scientists comparison does not decide

Compare Data Scientists listings by place

Washington

Exact location filter unavailable.

West Virginia

We could not load these listings.