California was 17.8% above the U.S. median for Data Scientists. It ranked 2 of 50 state areas with a published annual median. Neither comparison adjusts for cost of living, benefits, experience, employer mix, or hours.
Price-level context
What the local median may buy
BEA's 2024 all-items price index for California was 110.7, or 10.7% above the national price level. Its housing index was 154.3.
National-price-dollar proxy
$127,881
WageScope divides the published Data Scientists median by the BEA all-items index. This is a price-level comparison, not take-home pay, a personal budget, or a quality-of-life score.
Use the local pay range, same-source bench marks, job scale, price level, and survey care marks as separate facts. This guide stays tied to SOC 15-2051 and BLS area 06.
Questions, answered
Data Scientists pay in California: common questions
What is the median wage for Data Scientists in California?
The May 2025 BLS OEWS release published a median of $141,590 per year for Data Scientists in California. This describes an occupation-area estimate, not a promised offer or an individual's pay.
Is Data Scientists pay higher in California than nationally?
California's published median was 17.8% above the U.S. median for the same occupation and release.
Does the wage estimate adjust for cost of living in California?
No. The BLS wage is nominal. WageScope separately shows BEA's 2024 all-items Regional Price Parity of 110.7 and a transparent national-price-dollar proxy.
How many Data Scientists jobs does BLS estimate in California?
BLS published an employment estimate of 39,310 wage and salary jobs for this exact row. It is a survey estimate, not a current opening count or forecast.
From market data to your evidence
Tailor for a real Data Scientists job, not a generic wage number.
Pick an eligible listing, then MeritLog can help you prepare from experience you have confirmed. WageScope never turns a BLS estimate into a qualification or résumé claim.
What the Data Scientists median says in California
The May 2025 BLS OEWS estimate puts the Data Scientists median in California at $141,590 per year. Median means the middle of the published wage spread. It is not one worker's pay. It is not a job offer. The row is tied to SOC 15-2051 and BLS area 06.
BLS lists 39,310 wage and salary jobs for this exact role-place row. That is a survey estimate. It is not a count of open posts. The local mean is $156,000 per year. Mean uses all wage values behind the estimate, so high or low values can move it away from the median.
California's Data Scientists median is 17.8% above the U.S. Data Scientists median of $120,230 on the same published median. The comparison uses the same SOC code and source period. It does not add price levels, taxes, benefits, hours, or a person's work history.
This page exists because the BLS artifact has one row for SOC 15-2051 and area 06. SOC 15-2051 names Data Scientists. Area 06 names California. Both keys must match before WageScope can show or index this answer.
The 15-2051/06 row reports 39,310 wage and salary jobs, 2.16 jobs per 1,000 local jobs, and a 1.28 location quotient. Each value stays under the same two source keys.
For 15-2051/06, the annual median is $141,590 per year, while the matching mean is $156,000 per year. The row is published with annual and hourly fields. WageScope does not switch units to fill a blank.
BLS area 06 facts behind this Data Scientists page
Area 06 reports 18,213,700 wage and salary jobs across all covered occupations. Its annual mean is $80,690. Its annual median is $58,240. The employment RSE is 0%. The mean-wage RSE is 0.2%. These are facts for the whole area. They do not replace the 15-2051 row.
The all-jobs wage ladder in California runs from $35,950 at the 10th percentile to $159,080 at the 90th percentile. The 25th percentile is $41,600. The median is $58,240. The 75th percentile is $97,880. This is a place check, not a pay range for Data Scientists.
The source rows below are the six largest detailed roles in the bounded area file. Each keeps its own SOC code. They help a reader spot-check area 06. They do not show related skills or a path into Data Scientists.
1. Area 06, SOC 31-1120, Home Health and Personal Care Aides: 970,150 jobs, $34,320 annual median, 53.27 jobs per 1,000, and 1.92 location quotient.
2. Area 06, SOC 35-3023, Fast Food and Counter Workers: 449,840 jobs, $42,280 annual median, 24.7 jobs per 1,000, and 1 location quotient.
3. Area 06, SOC 41-2031, Retail Salespersons: 376,460 jobs, $38,440 annual median, 20.67 jobs per 1,000, and 0.82 location quotient.
Pay range
Read the California wage ladder for Data Scientists
The 10th percentile is $77,480 per year. The 25th percentile is $103,360 per year. The median is $141,590 per year. The 75th percentile is $186,820 per year. The 90th percentile is $224,920 per year.
A percentile is a rank point, not a career stage. The 10th percentile does not mean new-worker pay. The 90th percentile does not mean a wage that comes after a set number of years. The points show how the wage values spread in the source. They do not say why one job sits at one point.
The middle half runs from $103,360 per year to $186,820 per year. The 10th-to-90th span is $147,440. Use the full ladder when a job post sits far from the median.
California has a annual median of $141,590 per year. No exact state row is linked for this area. The U.S. row has $120,230 per year. WageScope keeps annual and hourly values apart.
A state comparison is not available for California. California is 17.8% above the United States on the same published median. A gap can reflect many things that are not in this row. WageScope reports the gap but does not name a cause.
The state and U.S. rows are bench marks, not replacements. They do not fill missing local facts. A state can hold many local labor markets. A national row can hold many states. Read the local row first, then use the broader rows to see scale.
California ranks 2 of 50 among states and territories with a published annual median for Data Scientists. The list keeps one SOC code, one map type, one wage metric, and one BLS release. It skips rows without the matching median.
Rank 2 of 50 is not a place score. A small wage gap can move a row several spots. The rank does not add local prices, job count, concentration, commute, taxes, or work rules. Use it only to find where the published median falls inside this like-for-like set.
The nearby rows below are the closest ranks, not chosen cities. Their pay, job counts, and local shares can differ. Open a peer page before making a deeper comparison. A title and one number are not enough for a move or pay choice.
1. Washington has a Data Scientists median of $163,350 per year, 9,600 estimated jobs, and a location quotient of 1.6.
3. Maryland has a Data Scientists median of $136,370 per year, 3,340 estimated jobs, and a location quotient of 0.72.
4. New Jersey has a Data Scientists median of $135,280 per year, 6,430 estimated jobs, and a location quotient of 0.89.
5. Massachusetts has a Data Scientists median of $131,750 per year, 9,420 estimated jobs, and a location quotient of 1.53.
Pay leaders
Where Data Scientists medians lead among states and territories
The rows below use the same SOC 15-2051, the same annual median, the same May 2025 BLS release, and the same state map type. Washington has the highest published median in this set, at $163,350 per year. California sits at $141,590 per year.
A pay lead is one fact. It does not show the size of the job base. It does not show how common Data Scientists is in the local mix. It also does not add local prices. The bullets keep the median, job count, and location quotient together so a high wage is not read as a full market score.
Use this list to choose a deeper pair, not to choose a place. Open the two local pages. Check the full wage ladder, the job scale, the survey care marks, and the exact BEA price row when present. A missing median stays out of this rank instead of becoming zero.
1. Washington has a Data Scientists median of $163,350 per year, or $21,760 above California. BLS lists 9,600 jobs there, compared with 39,310 in California. The location quotient is 1.6.
2. California has a Data Scientists median of $141,590 per year, or $0 above California. BLS lists 39,310 jobs there, compared with 39,310 in California. The location quotient is 1.28.
3. Maryland has a Data Scientists median of $136,370 per year, or $5,220 below California. BLS lists 3,340 jobs there, compared with 39,310 in California. The location quotient is 0.72.
Job-base leaders
Where BLS counts the most Data Scientists jobs
California has the largest published state job estimate for Data Scientists in this same-source set, at 39,310 jobs. California has 39,310. The count shows covered job scale, not open posts.
A large job base can have a lower median than a smaller one. It can also have a location quotient near or below 1. That is why WageScope does not blend job count, pay, and local share. Each field keeps its name and unit. The rows below let you compare all three without making one score.
Current MeritLog listings can add a dated view of employer-title matches. They do not change this May 2025 order. A place with few current cards can still have a large BLS job estimate. A place with several cards can still have a smaller estimate. The sources use different clocks and scopes.
1. California has 39,310 estimated Data Scientists jobs, a gap of 0 jobs from California. Its median is $141,590 per year, or $0 above California. Its location quotient is 1.28.
2. Texas has 25,860 estimated Data Scientists jobs, a gap of 13,450 jobs from California. Its median is $122,090 per year, or $19,500 below California. Its location quotient is 1.09.
3. New York has 23,970 estimated Data Scientists jobs, a gap of 15,340 jobs from California. Its median is $130,460 per year, or $11,130 below California. Its location quotient is 1.47.
Local-share leaders
Where Data Scientists takes the largest share of local jobs
District of Columbia has the highest published location quotient in this state set, at 2.27. California has 1.28. A value above 1 means the role's local job share is larger than its national share.
A high quotient can come from a small local job base. It does not prove more jobs, more posts, faster growth, or higher pay. The bullets keep each quotient beside its BLS job count and median. This lets a reader see when the three measures point in different ways.
Use this list to ask where Data Scientists is a large part of the local mix. Use the employment list to ask where BLS counts the most jobs. Use the pay list to ask where the median is highest. None of those lists decides where a person should work.
1. District of Columbia has a location quotient of 2.27, a gap of 0.99 from California. BLS lists 2,680 Data Scientists jobs and a median of $126,490 per year, or $15,100 below California.
2. Washington has a location quotient of 1.6, a gap of 0.32 from California. BLS lists 9,600 Data Scientists jobs and a median of $163,350 per year, or $21,760 above California.
3. Massachusetts has a location quotient of 1.53, a gap of 0.25 from California. BLS lists 9,420 Data Scientists jobs and a median of $131,750 per year, or $9,840 below California.
Job scale and share
How common Data Scientists is in California
BLS lists 39,310 Data Scientists jobs in California. It also lists 2.16 jobs per 1,000 local jobs. Jobs per 1,000 turns the count into a rate. It helps compare places of different size. It does not show open posts or hiring speed.
The location quotient is 1.28. A value of 1 means Data Scientists has the same share of local jobs as it has across the nation. This row is higher than 1. The quotient is a share check, not a wage or a growth measure.
Read the three values as separate facts. Employment asks how many covered jobs BLS estimated. Jobs per 1,000 asks how much of the local job base the role takes. Location quotient asks how that share compares with the national share. None of them tells you how many posts are open today.
The all-occupations median in California is $58,240 per year. The Data Scientists median is $141,590 per year. Data Scientists is 143.1% above the local all-occupations median on the same published median. This compares one role with the full covered job mix.
The nearby role medians below come from the bounded detailed-role table for California. They are close by wage, not by task. A small wage gap does not mean two jobs need the same skill or lead to the same career. Official titles keep their own SOC codes and source rows.
Use the list to spot the local wage mix around Data Scientists. Then open the role page you mean. A role can have a similar median and a very different job count or local share. The pay number alone cannot show fit, demand, or a path between jobs.
1. Registered Nurses, SOC 29-1141, has a California median of $140,270 per year. BLS lists 338,940 jobs and a location quotient of 0.86.
2. General and Operations Managers, SOC 11-1021, has a California median of $124,390 per year. BLS lists 300,840 jobs and a location quotient of 0.73.
3. Software Developers, SOC 15-1252, has a California median of $174,410 per year. BLS lists 284,390 jobs and a location quotient of 1.44.
Area job mix
The largest detailed roles in California
Home Health and Personal Care Aides is the largest detailed occupation in the bounded California table, at 970,150 jobs. Data Scientists has 39,310 jobs in its exact role-place row. The two counts show where this role sits beside other large parts of the local job base.
The all-occupations job count is 18,213,700. The detailed list below is only a bounded view of that larger mix. It does not sum to every local job. It does not include a blank role as zero. It helps explain why one role's wage and job count should not stand in for the whole area.
A large role can have a lower median. A smaller role can have a higher one. Job count does not show current posts, job quality, or growth. Use the list to see local scale. Then keep Data Scientists's own median, spread, and share in their own fields.
1. Home Health and Personal Care Aides has 970,150 jobs in California, a gap of 930,840 from Data Scientists. Its median is $34,320 per year, or $107,270 below Data Scientists. Its location quotient is 1.92.
2. Fast Food and Counter Workers has 449,840 jobs in California, a gap of 410,530 from Data Scientists. Its median is $42,280 per year, or $99,310 below Data Scientists. Its location quotient is 1.
Area pay mix
Published role medians around California
Software Developers has the highest published median in the bounded California role table, at $174,410 per year. Data Scientists has $141,590 per year. This puts the role beside a local pay range without blending the source rows.
The local all-occupations median is $58,240 per year. A role above that mark is not better. A role below it is not worse. The mark only shows where the role's published median sits against the full covered job mix. Job tasks, level, hours, and work setting are separate facts.
The bullets keep each SOC title, job count, median, and local share together. Use them to find a role page worth opening. Do not use a close median as proof that two roles share skills or that one is a path to the other.
1. Software Developers has a median of $174,410 per year in California, or $32,820 above Data Scientists. BLS lists 284,390 jobs, compared with 39,310 for Data Scientists. Its location quotient is 1.44.
2. Registered Nurses has a median of $140,270 per year in California, or $1,320 below Data Scientists. BLS lists 338,940 jobs, compared with 39,310 for Data Scientists. Its location quotient is 0.86.
3. General and Operations Managers has a median of $124,390 per year in California, or $17,200 below Data Scientists. BLS lists 300,840 jobs, compared with 39,310 for Data Scientists. Its location quotient is 0.73.
Area role shares
Roles with the largest local share in California
Farmworkers and Laborers, Crop, Nursery, and Greenhouse has the highest location quotient in the bounded California role table, at 5.54. Data Scientists has 1.28. Both values compare a local job share with the matching national share.
A quotient above 1 means the role takes a larger share of local jobs than it does across the nation. It does not mean more jobs than every other role. It does not mean open posts, growth, or high pay. The job count and median beside each row answer those other narrow questions.
The local role-share mix can differ a lot from the pay mix. Read both lists. Then compare Data Scientists with the same SOC code in another place. This keeps a broad area pattern from replacing the exact role-place row.
1. Farmworkers and Laborers, Crop, Nursery, and Greenhouse has a location quotient of 5.54 in California, a gap of 4.26 from Data Scientists. BLS lists 172,260 jobs and a median of $35,580 per year, or $106,010 below Data Scientists.
2. Home Health and Personal Care Aides has a location quotient of 1.92 in California, a gap of 0.64 from Data Scientists. BLS lists 970,150 jobs and a median of $34,320 per year, or $107,270 below Data Scientists.
Price-level view
What $141,590 may mean after the California price level
BEA's 2024 all-items price index for California is 110.7. The U.S. level is 100. The local level is 10.7% above that mark. This is a broad price comparison. It is not a personal budget.
WageScope divides the $141,590 Data Scientists median by 110.7 divided by 100. The result is $127,881 in national-price dollars per year. This proxy keeps the math clear. It is not take-home pay and does not set a move target.
Housing is 154.3. Goods are 106.1. Utilities are 158.9. Other services are 102.6. The parts do not move as one. WageScope uses BEA's all-items index for the proxy and does not make its own basket.
The employment RSE for this Data Scientists row is 4.3%. The mean-wage RSE is 2.6%. RSE means relative standard error. It is a survey precision flag. A smaller value often means less sampling uncertainty. It is not the chance that one person's pay is right or wrong.
The employment RSE belongs to the 39,310 job estimate. The mean-wage RSE belongs to the $156,000 mean. BLS does not give the same RSE field for the median or every percentile. WageScope does not move an RSE from one field to another.
A local row can change in a new release. A small role-place sample can also have more survey uncertainty than a broad national row. Keep the May 2025 date next to the value. Do not mix a newer job post with the BLS date as if both facts came from one clock.
The job block looks for strict employer-title matches to Data Scientists. It uses a California place filter only when the public place list has an exact approved match. If that match is not safe, the page says the jobs are not narrowed to this place. A false negative is safer than showing a different role.
Each card keeps its employer, place, source, and seen date. Listings can change between visits while the survey figures stay tied to their release date. A listing range does not replace the $141,590 BLS median. The listing and survey answer different questions.
Open one listing. Check its level, work place, pay range, and needs. Then tailor with work facts you can support. Do not turn a wage, job count, rank, or price proxy into a résumé claim. The public page is read only. It does not save a job or start a draft on load.
What the Data Scientists row for California does not claim
The row does not say what one person earns. It does not promise a job, offer, raise, or move result. It does not say why the local median differs from the U.S. row. It does not add tips, bonus pay, stock, benefits, taxes, or work hours unless those items are in the BLS wage measure.
The 39,310 job estimate is not a live opening count. The location quotient of 1.28 is not a growth score. Rank 2 of 50 is not a place score. The 110.7 price index is not a personal budget.
Use the row for one clear task. Read the May 2025 wage spread for SOC 15-2051 in BLS area 06. Compare the same metric with the state and U.S. rows. Add the separate 2024 price level when present. Inspect a dated job match. Then use confirmed work facts for a résumé.
Are the current job listings included in the BLS wage calculation?
No. MeritLog shows eligible live public-catalog listings separately, with their own source and observation date. Posted pay never changes the official BLS distribution.
4. Area 06, SOC 53-7062, Laborers and Freight, Stock, and Material Movers, Hand: 355,500 jobs, $44,710 annual median, 19.52 jobs per 1,000, and 1.03 location quotient.
5. Area 06, SOC 29-1141, Registered Nurses: 338,940 jobs, $140,270 annual median, 18.61 jobs per 1,000, and 0.86 location quotient.
6. Area 06, SOC 41-2011, Cashiers: 336,110 jobs, $37,100 annual median, 18.45 jobs per 1,000, and 0.93 location quotient.
4. New Jersey has a Data Scientists median of $135,280 per year, or $6,310 below California. BLS lists 6,430 jobs there, compared with 39,310 in California. The location quotient is 0.89.
5. Massachusetts has a Data Scientists median of $131,750 per year, or $9,840 below California. BLS lists 9,420 jobs there, compared with 39,310 in California. The location quotient is 1.53.
6. New York has a Data Scientists median of $130,460 per year, or $11,130 below California. BLS lists 23,970 jobs there, compared with 39,310 in California. The location quotient is 1.47.
7. Minnesota has a Data Scientists median of $128,800 per year, or $12,790 below California. BLS lists 4,020 jobs there, compared with 39,310 in California. The location quotient is 0.81.
8. Vermont has a Data Scientists median of $127,070 per year, or $14,520 below California. BLS lists 200 jobs there, compared with 39,310 in California. The location quotient is 0.38.
4. Pennsylvania has 13,810 estimated Data Scientists jobs, a gap of 25,500 jobs from California. Its median is $106,850 per year, or $34,740 below California. Its location quotient is 1.35.
5. North Carolina has 11,430 estimated Data Scientists jobs, a gap of 27,880 jobs from California. Its median is $119,090 per year, or $22,500 below California. Its location quotient is 1.37.
6. Illinois has 10,520 estimated Data Scientists jobs, a gap of 28,790 jobs from California. Its median is $106,560 per year, or $35,030 below California. Its location quotient is 1.02.
7. Florida has 10,240 estimated Data Scientists jobs, a gap of 29,070 jobs from California. Its median is $115,820 per year, or $25,770 below California. Its location quotient is 0.61.
8. Washington has 9,600 estimated Data Scientists jobs, a gap of 29,710 jobs from California. Its median is $163,350 per year, or $21,760 above California. Its location quotient is 1.6.
4. Utah has a location quotient of 1.49, a gap of 0.21 from California. BLS lists 4,360 Data Scientists jobs and a median of $108,090 per year, or $33,500 below California.
5. New York has a location quotient of 1.47, a gap of 0.19 from California. BLS lists 23,970 Data Scientists jobs and a median of $130,460 per year, or $11,130 below California.
6. North Carolina has a location quotient of 1.37, a gap of 0.09 from California. BLS lists 11,430 Data Scientists jobs and a median of $119,090 per year, or $22,500 below California.
7. Rhode Island has a location quotient of 1.37, a gap of 0.09 from California. BLS lists 1,160 Data Scientists jobs and a median of $102,440 per year, or $39,150 below California.
8. Pennsylvania has a location quotient of 1.35, a gap of 0.07 from California. BLS lists 13,810 Data Scientists jobs and a median of $106,850 per year, or $34,740 below California.
4. Management Analysts, SOC 13-1111, has a California median of $101,460 per year. BLS lists 137,280 jobs and a location quotient of 1.3.
5. Elementary School Teachers, Except Special Education, SOC 25-2021, has a California median of $99,650 per year. BLS lists 155,160 jobs and a location quotient of 0.95.
6. Accountants and Auditors, SOC 13-2011, has a California median of $97,050 per year. BLS lists 175,360 jobs and a location quotient of 1.03.
7. Business Operations Specialists, All Other, SOC 13-1199, has a California median of $87,570 per year. BLS lists 155,000 jobs and a location quotient of 1.22.
8. Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel, SOC 41-3091, has a California median of $80,850 per year. BLS lists 156,110 jobs and a location quotient of 1.06.
3. Retail Salespersons has 376,460 jobs in California, a gap of 337,150 from Data Scientists. Its median is $38,440 per year, or $103,150 below Data Scientists. Its location quotient is 0.82.
4. Laborers and Freight, Stock, and Material Movers, Hand has 355,500 jobs in California, a gap of 316,190 from Data Scientists. Its median is $44,710 per year, or $96,880 below Data Scientists. Its location quotient is 1.03.
5. Registered Nurses has 338,940 jobs in California, a gap of 299,630 from Data Scientists. Its median is $140,270 per year, or $1,320 below Data Scientists. Its location quotient is 0.86.
6. Cashiers has 336,110 jobs in California, a gap of 296,800 from Data Scientists. Its median is $37,100 per year, or $104,490 below Data Scientists. Its location quotient is 0.93.
7. Office Clerks, General has 311,490 jobs in California, a gap of 272,180 from Data Scientists. Its median is $48,460 per year, or $93,130 below Data Scientists. Its location quotient is 1.08.
8. Stockers and Order Fillers has 310,870 jobs in California, a gap of 271,560 from Data Scientists. Its median is $42,870 per year, or $98,720 below Data Scientists. Its location quotient is 0.94.
4. Management Analysts has a median of $101,460 per year in California, or $40,130 below Data Scientists. BLS lists 137,280 jobs, compared with 39,310 for Data Scientists. Its location quotient is 1.3.
5. Elementary School Teachers, Except Special Education has a median of $99,650 per year in California, or $41,940 below Data Scientists. BLS lists 155,160 jobs, compared with 39,310 for Data Scientists. Its location quotient is 0.95.
6. Accountants and Auditors has a median of $97,050 per year in California, or $44,540 below Data Scientists. BLS lists 175,360 jobs, compared with 39,310 for Data Scientists. Its location quotient is 1.03.
7. Business Operations Specialists, All Other has a median of $87,570 per year in California, or $54,020 below Data Scientists. BLS lists 155,000 jobs, compared with 39,310 for Data Scientists. Its location quotient is 1.22.
8. Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel has a median of $80,850 per year in California, or $60,740 below Data Scientists. BLS lists 156,110 jobs, compared with 39,310 for Data Scientists. Its location quotient is 1.06.
3. Cooks, Fast Food has a location quotient of 1.66 in California, a gap of 0.38 from Data Scientists. BLS lists 124,440 jobs and a median of $42,050 per year, or $99,540 below Data Scientists.
4. Software Developers has a location quotient of 1.44 in California, a gap of 0.16 from Data Scientists. BLS lists 284,390 jobs and a median of $174,410 per year, or $32,820 above Data Scientists.
5. Security Guards has a location quotient of 1.33 in California, a gap of 0.05 from Data Scientists. BLS lists 199,480 jobs and a median of $43,240 per year, or $98,350 below Data Scientists.
6. Management Analysts has a location quotient of 1.3 in California, a gap of 0.02 from Data Scientists. BLS lists 137,280 jobs and a median of $101,460 per year, or $40,130 below Data Scientists.
7. Business Operations Specialists, All Other has a location quotient of 1.22 in California, a gap of 0.06 from Data Scientists. BLS lists 155,000 jobs and a median of $87,570 per year, or $54,020 below Data Scientists.
8. Office Clerks, General has a location quotient of 1.08 in California, a gap of 0.20 from Data Scientists. BLS lists 311,490 jobs and a median of $48,460 per year, or $93,130 below Data Scientists.
Precise employer-title matches for Data Scientists in California
Filtered through MeritLog's approved California place record and a strict employer-title rule. Listings are not classified by BLS and remain separate from BLS and BEA estimates.
