Data Scientist Salary in Dallas — 2026 BLS Data
Salary distribution
Percentile breakdown of Data Scientist base salaries in Dallas.
The BLS OEWS May 2024 data for the Dallas-Fort Worth-Arlington MSA puts the median data scientist base salary at $120,840 — about 7% above the national median of $112,590 for the same occupation code (SOC 15-2051). That premium is real but modest, and it doesn’t capture the full picture. The DFW market is unusual because it sits at an intersection of corporate finance, telecom, transportation, and growing tech that produces a compensation spread far wider than a single number suggests. A quant-adjacent risk modeler at JPMorgan Chase’s Plano campus and a junior analytics DS at a regional hospital system technically hold the same job title, but their offers look nothing alike.
Dallas data scientist salary percentiles (BLS OEWS May 2024)
The Dallas-Fort Worth-Arlington MSA data from BLS OEWS 2024, accessed via O*NET’s regional wage tables, breaks down as follows:
| Percentile | Annual Base Salary |
|---|---|
| 25th (P25) | $84,710 |
| 50th (P50, median) | $120,840 |
| 75th (P75) | $140,840 |
| 90th (P90) | $172,160 |
The P25-to-P90 spread of roughly $87K inside a single metropolitan labor market is the first thing worth examining. Nationally, the same spread for this occupation runs about $112K (P25 $82,630 to P90 $194,410). Dallas’s narrower spread reflects a market where the floor is slightly higher than the national average — there are fewer poverty-wage “data science” roles getting dragged into the distribution — but the ceiling is lower than tech-heavy metros like San Francisco or Seattle. The P90 in Dallas ($172K) is about $22K below the national P90. That gap is the tech-company premium that Dallas still lacks at scale relative to the Bay Area.
What the median hides
The $120,840 median is a statistical midpoint across a wildly heterogeneous pool. BLS doesn’t break out job levels, company tiers, or specialties within SOC 15-2051 — it aggregates everyone. A few dynamics that the single number obscures:
Industry vertical shapes the number more than experience. DFW’s data science job market is dominated by a handful of large corporate sectors: financial services (JPMorgan Chase, Goldman Sachs, Citi, Capital One), telecom and tech (AT&T, Samsung’s US HQ in Plano), transportation and logistics (American Airlines, Southwest Airlines, Toyota’s North American HQ), healthcare, and a growing mid-market SaaS corridor. Financial services and tech roles cluster toward P75-P90 ($140K–$172K+). Healthcare, logistics support roles, and state/local government roles cluster near or below the median. If you’re targeting banking or tech, $120K is the floor for a competent mid-level hire, not the target.
Level compression makes the lower percentiles misleading. The P25 of $84,710 includes early-career DS roles (0–2 years of experience) at companies that haven’t yet calibrated their DS pay to market. Texas has no state income tax, which sometimes causes smaller employers to justify lower gross pay. A data scientist with three years of strong experience building production ML models should not be accepting anywhere near the P25 — that number should be a flag, not a benchmark.
Remote work pollutes the local sample. Some DFW-based professionals appear in the OEWS data while earning coastal pay from remote-first companies. This skews P75 and P90 upward slightly relative to what a purely Dallas-headquartered employer would offer. It also means the percentiles describe the distribution of what DFW residents earn, not strictly what DFW employers pay.
How Dallas compares to other major data science hubs
Dallas is a second-tier market for data science compensation — above the national median but well below the West Coast majors. Framing the comparison properly requires adjusting for cost of living, not just gross salary.
San Francisco sits at a COL index of roughly 178, with a data scientist median closer to $175K–$190K base at the market midpoint. Total comp (base plus equity) at a mid-level DS role routinely clears $250K. But SF housing, state income tax, and general cost of living consume most of that premium. The COL-adjusted purchasing power advantage over Dallas narrows sharply.
Seattle (COL index ~135) pays data scientists a median of roughly $145K–$160K base. The tech-heavy employer base (Amazon, Microsoft, Tableau/Salesforce) produces more equity-heavy packages than Dallas.
Austin (COL index ~119) offers a data scientist median of around $115K–$120K — essentially matching Dallas — but with a concentration of high-growth tech employers (Tesla, Oracle, Apple, Indeed) that pushes the upper tail higher than DFW’s. Austin’s P90 runs closer to $180K–$200K due to that tech-employer density.
New York City (COL index ~187) tops out the highest on gross figures, with finance-adjacent DS roles at quant funds and major banks routinely paying $180K–$240K base. But NYC’s cost structure, state income tax, and city tax erode those numbers considerably.
The honest read: on a cost-of-living-adjusted basis, a strong P75 offer in Dallas ($140K–$150K base, no state income tax) compares favorably to a median SF or NYC offer once you account for what you actually keep.
What drives the spread: company tier, level, and specialty
Three variables explain the bulk of the $87K gap from P25 to P90 inside Dallas:
Company tier
The DFW corporate hierarchy for data science pay is roughly:
- Top tier ($145K–$200K+ base): Financial services firms with quant functions (JPMorgan Chase data science roles in Plano run $98K–$187K per Levels.fyi data), tech companies with dedicated ML infrastructure, and large-cap tech adjacent roles (Samsung Research America, AT&T technology labs).
- Mid tier ($110K–$145K): Mid-market SaaS, major airlines (DS roles at American and Southwest Airlines that blend analytics with operations research), and healthcare systems with mature data organizations.
- Lower tier ($75K–$110K): Retail, regional healthcare, insurance, government contractor, and consulting roles where “data scientist” is often a glorified BI analyst title. These populate the P25 heavily.
Company-tier selection is the single highest-leverage variable for a DS in DFW. Moving from a mid-tier employer to a financial services or tech-adjacent role at the same experience level typically adds $20K–$40K in base salary.
Level and experience
Dallas employers are more likely than coastal ones to formalize DS levels as DS I, DS II, Senior DS, Lead/Principal DS. The pay step-up per level runs roughly:
- DS I (0–2 YOE): $75K–$95K
- DS II (2–4 YOE): $95K–$120K
- Senior DS (4–7 YOE): $120K–$150K
- Lead/Principal DS (7+ YOE, technical leadership scope): $150K–$185K+
At the senior and above levels, companies expect production ML experience — models deployed to production environments, not just notebooks and dashboards. That specific credential separates the top-of-band offers from mid-band.
Specialty
ML engineering and applied AI roles command a meaningful premium over generalist DS work in Dallas:
- ML Engineer (production focus): $140K–$170K median per Indeed data for Dallas, reflecting the scarcity of engineers who can both model and deploy.
- NLP / LLM specialist: $130K–$160K, with demand accelerating in 2025–2026 as AT&T, JPMorgan, and healthcare systems build out AI tooling.
- Computer vision / perception: Concentrated at Samsung Research America (Plano) and automotive tech suppliers; $130K–$165K.
- Analytics / BI-heavy DS: $90K–$115K. These are the roles that populate the lower half of the OEWS distribution and are most likely to be mislabeled as data science.
If you’re interviewing for a “data scientist” role, ask in the first screening call: “How many models does your team currently have running in production?” A company with zero or one will pay you analytics wages regardless of what the title says.
Total compensation: beyond the base
BLS OEWS tracks only wages — it excludes bonuses, equity, and benefits entirely. For data scientists, the gap between base salary and total compensation is meaningful, particularly at higher levels and in financial services.
A mid-level DS at a representative DFW employer (say, a financial services firm or major tech company) might see a package structured like this:
- Base salary: $120,840. This is the BLS number — what shows up on your W-2’s wages line and what base cash budgeting runs against.
- Annual performance bonus: ~$18,000. Typical DS bonus pools run 10–20% of base at large corporates. Financial services skews higher (15–25%); tech and healthcare skew lower (8–15%). Target bonus percentages are usually published in the offer letter.
- Equity / RSUs: ~$15,000 annualized. Dallas is not an equity-heavy market by default — most large DFW employers are publicly traded corporations where DS roles receive RSU grants that vest over 3–4 years, not the concentrated equity stakes common at Bay Area startups. At a large bank or airline, a mid-level DS might receive an initial RSU grant of $45K–$80K vesting over four years. At tech-adjacent companies with higher growth profiles, grants scale up.
That puts representative total comp for a median DS in DFW at roughly $154K. Senior DS roles ($145K–$165K base) with 15–20% bonus plus RSUs can reach $190K–$220K total comp. At financial services firms specifically — JPMorgan, Goldman, Citi — cash-heavy compensation structures mean bonus can match or exceed the equity component, which is the inverse of West Coast tech.
Texas has no state income tax (compared to 9.3% in California or 6.85%+ in New York), which effectively adds $6,000–$8,000 to take-home for a median-earning DS relative to those states. That’s a real number that often goes unacknowledged in coastal-to-DFW comparisons.
Cost-of-living adjusted picture
Dallas’s COL index of 94 means the DFW metro runs about 6% below the US national average. Housing is the dominant driver: the median single-family home in DFW was around $360,000–$380,000 in early 2026, versus $1.1M+ in San Francisco and $600K in Denver. A one-bedroom apartment in Dallas runs $1,400–$1,600/month near corporate corridors.
Working through the math on purchasing power: a $120,840 Dallas base is equivalent in real purchasing power to roughly $128,500 at the US national average. Compared to San Francisco (COL 178), that same $120K has the buying power of a $214K San Francisco salary. Compared to Austin (COL 119), it’s within 5% — the two Texas metros are close to parity on a COL-adjusted basis, with Dallas having the slight COL advantage and Austin having the higher-earning tech-employer base.
The no-state-income-tax factor compounds this. At $120,840 gross, a Texas employee keeps roughly $8,700–$10,500 more per year than a California counterpart at the same gross wage (depending on deductions and filing status). That’s not trivial — it’s equivalent to a 7–9% base salary increase.
Three-lever negotiation playbook for DS roles in DFW
The Dallas market has its own negotiation dynamics. Unlike Bay Area tech where equity is the primary battleground, DFW negotiations typically center on base salary and bonus structure, with equity a secondary consideration for most employers.
Lever 1: Anchor to P75, not the median
The BLS median ($120,840) is almost certainly below what you should be targeting unless you are genuinely early-career or pivoting industries. If you have three or more years of relevant experience and production ML work to show, the P75 of $140,840 is the appropriate anchor for your first number. Research shows that candidates who anchor to their researched market high-water mark — rather than leaving the first number to the employer — close 8–15% higher on average in salary negotiations. State the number crisply: “Based on my research on BLS OEWS for the DFW metro and comparable offers I’ve seen, I’m looking for a base around $140K.” Specificity signals you’ve done the work.
Lever 2: Push hard on the bonus target percentage
In DFW corporate environments, bonus is often more flexible than base salary, particularly at large employers where base bands are tightly managed by HR systems. A shift from a 10% target bonus to a 15% target bonus on a $130K base is $6,500 per year — equivalent to a $6K raise — but it often faces less organizational resistance because it’s framed as performance-contingent. Ask for the bonus target in writing in the offer letter, and if the initial percentage is below market for the industry (10% at a bank, say), push for 12–15% explicitly: “For a DS role in financial services, I’ve seen 15% target bonuses fairly consistently. Is there flexibility there?”
Lever 3: Negotiate the initial RSU grant, not the annualized value
Most Dallas corporate employers quote equity in the offer letter as an annualized number (“$15K/year in RSUs”) rather than the total grant, which obscures the negotiation surface. Ask for the total grant amount and vesting schedule. A $60K grant vesting over four years is psychologically more real than “$15K/year,” and larger total grants are easier to negotiate at offer time than in annual review cycles. At senior DS levels, pushing the initial grant from $60K to $80K total — $20K in new equity — is a common successful ask because equity is less constrained than base salary bands at most large-cap employers.
One additional note: if you hold a competing offer from a financial services firm or tech company, disclose it to the recruiter concretely. DFW recruiters respond well to competing offers — they know the talent pool for production ML is tight — but they need a specific number to take to their comp team. “I have another offer in hand at $145K base” is far more actionable than “I’m considering other opportunities.”
Data caveats
BLS OEWS is the most reliable public-domain salary dataset available, but several limitations apply specifically to this occupation and market:
Equity is excluded entirely. The BLS tracks wages only. For data scientists at financial services firms or tech companies with meaningful RSU grants, total compensation runs $15,000–$50,000 above the OEWS figures depending on level. The percentiles above describe cash compensation only.
The data is lagged. The May 2024 release reflects wages paid in 2024. Market rates for ML-specialized roles in particular have moved measurably since then, with LLM and AI platform skills commanding growing premiums through 2025–2026. Add roughly 5–8% to the upper percentiles for current market conditions if you have in-demand AI skills.
SOC 15-2051 is broad. It covers roles from junior analytics data scientists to principal ML engineers, and spans industries from healthcare to banking to retail. The percentiles are genuine but they describe a heterogeneous group. Triangulate OEWS data against published salary ranges in Texas job postings (Texas does not require salary transparency legislation, but many large employers include ranges voluntarily) and Levels.fyi data for named DFW-area employers.
The MSA boundary matters. The Dallas-Fort Worth-Arlington MSA is large — it includes Plano, Frisco, Irving, and Allen, where many major corporate campuses sit. Employers physically in downtown Dallas proper represent a different mix than the suburban corridors. The wage data pools all of them.
For a complete picture, supplement BLS OEWS with O*NET’s local wage tool (which sources the same data in a more accessible format), Levels.fyi for named employer data at tech and finance firms, and actual posted ranges in job descriptions. Between those three sources, you can get within 8–10% of what any specific offer in DFW should look like before you walk into the room.
If you’re actively tracking job applications alongside your salary research — comparing offers, monitoring application status, keeping notes on each company’s comp structure — a dedicated job tracker keeps all of that organized in one place rather than scattered across browser tabs and spreadsheets.