Data Scientist Salary in Texas: Pay by Experience, City & Take-Home

A data scientist in Texas earns a median salary of $122,090 a year, about $58.70 an hour, according to the U.S. Bureau of Labor Statistics (2025). Most of the field lands between $83,880 (25th percentile) and $146,030 (75th percentile), and the top 10 percent clear $170,780. Texas pays slightly above the national median and charges no state income tax, which changes the take-home math more than the gross number suggests.

How Texas compares to the national median

The national median for data scientists is $120,230, per the BLS. Texas sits at $122,090, so the typical data scientist here earns $1,860 more than the national midpoint. That gap is small on paper, but Texas does the real work after tax. With no state income tax, more of that $122,090 stays in your account than it would in a state like California or New York that taxes the same gross at 9 percent or higher.

The field is also deep in Texas. The state employs roughly 25,860 data scientists, one of the larger concentrations in the country, which gives you bargaining power on competing offers and a real market to move between without leaving the state. The spread is wide: the 10th percentile earns $64,540 while the 90th clears $170,780. Where you land inside that band depends mostly on experience, metro, and whether you work for a tech employer or a more traditional one.

It helps to read the national gap the right way. A $1,860 edge over the U.S. median sounds modest, and on the gross line it is. But the national median rolls together high-tax states like California and New York with no-tax states like Texas and Florida. Once you adjust for what each state takes back at the state level, Texas pulls well ahead of the average rather than just inching past it. That is why the take-home section below carries more weight than the headline comparison here: the gross numbers are close, but the after-tax numbers are not.

The full Texas range runs from $64,540 at the 10th percentile to $170,780 at the 90th, a spread of $106,240. That is a very wide band for a single occupation in a single state, and it reflects how much the title covers. A junior analyst building dashboards and a staff data scientist owning a recommendation system in production both carry the same SOC code (15-2051), so the percentile you target tells you far more about your likely pay than the job title alone.

Data scientist salary in Texas by experience

Pay scales hard with experience in this role. Entry-level analysts and new grads cluster near the 10th to 25th percentile. Mid-career data scientists sit around the median, and senior or staff-level people with a track record of shipping models into production reach the 75th to 90th percentile. Here is the full curve from the BLS percentile data.

The jump from early career to the median is the steepest part of the curve: about $38,210 over a few years as you move from cleaning data and building dashboards to owning models end to end. After the median, raises come slower and tend to require either a move into staff-level individual contribution, a management track, or a switch to a higher-paying employer. The mean salary statewide is $119,710, a touch below the median, which tells you the distribution has a long upper tail pulled by senior roles rather than a cluster of very high earners dragging everyone up.

Read the gaps between stages and you can plan a whole career. Entry to early career is worth about $19,340 (from $64,540 to $83,880). Early career to the median adds another $38,210. The median to the experienced 75th percentile is $23,940, and the final climb to the senior 90th percentile is $24,750. The biggest single raise sits in the middle of the curve, which is exactly the stretch where switching employers or specializing pays off most. People who stay in one seat through those years tend to underearn, because the steepest part of the curve rewards the move into model ownership, and that move usually comes with a new title or a new company.

One practical note on the entry figure. The $64,540 at the 10th percentile often reflects either a first-job analyst title or a non-tech employer using “data scientist” loosely. A new graduate with a strong portfolio and a Texas tech employer can frequently start closer to the 25th percentile of $83,880 rather than the floor. Treat the 10th percentile as the bottom of the realistic range, not the expected offer, and anchor your negotiation to the early-career number instead.

Data scientist salary by Texas metro

Where you work inside Texas matters more than people expect. The Dallas-Fort Worth and Austin metros pay roughly $20,000 to $32,000 more at the median than San Antonio or El Paso. This is the section national averages and AI summaries get wrong, because the real number is local.

Dallas-Fort Worth is both the highest-paying major metro at $127,750 and by far the largest market, with 10,120 data scientists employed. That combination of pay and depth makes it the strongest base in the state for the role. Austin runs nearly even at $127,360 and carries a tech-heavy employer mix, so the upside above the median is often better there than the flat figure suggests.

Houston, despite being a huge metro, posts a lower median of $106,750. A lot of that reflects the employer mix: energy, healthcare, and industrial firms staff data science teams differently than pure tech companies do. San Antonio ($103,290) and El Paso ($95,430) round out the bottom, and El Paso’s small headcount of 320 means individual offers there vary widely. If you are mobile, moving a data science job from El Paso to Dallas can add more than $32,000 to your gross before you account for the cost-of-living difference.

The employment numbers tell their own story. DFW alone holds 10,120 of the state’s 25,860 data scientists, roughly 39 percent of the entire Texas market in one metro. Add Houston’s 4,060 and Austin’s 3,730 and those three metros account for about 17,910 jobs, the bulk of the field. That concentration matters for job security and mobility: in DFW or Austin you can change employers without changing cities, which is the single most reliable way to jump from the median to the 75th percentile. In El Paso, with only 320 roles, a single employer’s hiring freeze can shift the whole local market.

One more way to read the metro table: Dallas pays $5,660 above the state median and $21,520 above the national median, while El Paso pays $26,660 below the state median. That is a $32,320 swing within the same state and the same job title. National salary tools and AI overviews almost always quote a single statewide or national figure, which is why bringing the exact metro median into a negotiation is one of the highest-impact things a Texas data scientist can do.

Take-home pay after taxes in Texas

Gross salary is the headline. Take-home is the number that lands in your account. Texas charges no state income tax, so a data scientist here keeps everything except federal income tax and FICA (Social Security and Medicare). Here is the breakdown at four points on the salary curve, using 2026 tax assumptions for a single filer.

At the median, a Texas data scientist takes home $94,202 a year, or $7,850 a month, after an effective tax rate of about 22.8 percent. The state-tax column is $0 across every row, and that zero is the whole point of working this job in Texas rather than a high-tax state.

Notice how the effective rate climbs with income but stays reasonable. The entry earner at $64,540 keeps $53,790, an effective rate of about 16.7 percent. The median earner pays 22.8 percent, the experienced 75th-percentile earner at $146,030 pays about 24.3 percent and nets $110,565, and the senior 90th-percentile earner at $170,780 pays roughly 25.4 percent and still takes home $127,481. Because there is no state layer, the only thing pushing your effective rate up is the federal bracket structure, so the climb is gradual rather than a cliff. In a high-tax state, that same income would stack a state bracket on top of federal, and the gap between stages would widen.

Here is the comparison that matters. Take the exact same $122,090 median salary and run it through California’s tax code. A data scientist there nets about $86,820, against $94,202 in Texas. That is a gap of $7,382 a year in your pocket for identical gross pay, purely because Texas has no state income tax. Over a five-year stretch that is more than $36,000, enough to fund a serious chunk of a down payment or a maxed-out retirement contribution.

One caveat keeps the comparison honest: net pay minus local housing is the number that actually decides your standard of living. A higher take-home in Dallas does little good if rent eats the difference, so weigh that $7,382 advantage against what a comparable home or apartment costs in each metro. In most of Texas the housing math still comes out ahead of coastal California, which is a big part of why the field has grown here. To pressure-test your own numbers, run them through the Texas paycheck calculator, and if you want help modeling deductions or a side-income return, TurboTax walks through the federal side cleanly.

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How to earn more as a data scientist in Texas

The data shows clear levers. The move from the median ($122,090) to the 75th percentile ($146,030) is worth about $23,940 a year, and reaching the 90th ($170,780) adds another $24,750. Here is how people actually close that gap in this state.

• Base yourself in Dallas-Fort Worth or Austin. Both pay a median near $127,750 versus $103,290 in San Antonio or $95,430 in El Paso. Relocating within Texas can add $20,000 to $32,000 to your gross with zero change in tax treatment.
• Move toward production machine learning. The pay tail above the median rewards people who ship models into live systems rather than producing reports. Owning deployment, monitoring, and the data pipeline is what separates a $122,000 role from a $170,000 one.
• Pick the right employer mix. Austin’s tech-heavy market and DFW’s mix of corporate and tech employers tend to push offers higher than Houston’s energy and industrial firms at the same title.
• Add credentials that map to higher-paying work. Cloud (AWS, GCP, Azure) machine-learning certifications and a strong portfolio in deep learning or MLOps move you up the band. Structured courses through Coursera are a low-cost way to build the AWS or TensorFlow credentials employers screen for.
• Negotiate against the local median, not the national one. Texas pays $1,860 above the U.S. median and DFW pays $5,660 above the state median. Walking into a negotiation with the exact metro figure is worth more than a generic salary range.
• Use the no-tax advantage in your math, not your offer. An out-of-state recruiter may quote a California number that looks higher on paper. Convert both to take-home before you decide. A $122,090 Texas offer nets $94,202, and it can beat a higher California gross once that state’s income tax comes out. Frame your decisions around net, not headline gross.

The pattern across all of these levers is the same: the Texas market rewards specialization and location far more than it rewards tenure in one seat. The data scientists who reach the $146,030 to $170,780 range almost always did one of three things. They moved into production machine learning, they relocated to DFW or Austin, or they changed employers at the point where their current one capped out near the median. Stacking two of those moves is how people clear the 90th percentile before the typical career timeline would suggest.

Job outlook for data scientists in Texas

Data science is one of the fastest-growing occupations the BLS tracks nationally, and Texas is a focal point of that growth. The state already employs about 25,860 data scientists, and the concentration in Dallas-Fort Worth (10,120), Houston (4,060), and Austin (3,730) shows a market deep enough to sustain real career mobility. Demand spans tech, finance, energy, healthcare, and logistics, so you are not tied to a single industry’s hiring cycle. When you are ready to test the market, ZipRecruiter aggregates Texas data science openings across those metros in one place.

Related and higher-paying roles in Texas

If you are weighing adjacent paths, here is how they stack up against the $122,090 data scientist median in Texas, using BLS state medians. A software developer earns a median of $132,150, which is $10,060 more than a data scientist here. A computer systems analyst earns $107,390, which is $14,700 less. Software development edges out data science on median pay in Texas, while systems analysis trades some pay for a broader, more business-facing role.

Data scientist salary in Texas: FAQ

Sources: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics (OEWS) 2025; ThePayGuide 2026 tax modeling (single filer, federal income tax and FICA). Last updated 2026. See our methodology.