Data Scientist Salary in Houston — 2026 BLS Data

$100K median base salary · Houston
BLS OEWS · 2024 data

Salary distribution

Percentile breakdown of Data Scientist base salaries in Houston.

The BLS OEWS May 2024 release puts the median base salary for a Data Scientist (SOC 15-2051) in the Houston-Pasadena-The Woodlands metro at $100,420. That number is accurate, and it’s also incomplete. It reflects everyone from an analytics hire at a regional hospital system to a senior ML engineer at an ExxonMobil digital transformation team — roles with different scope, different comp structures, and different career trajectories. The $100,420 median is a reasonable floor for gauging whether an offer is in the market, not a target to accept and call it good. This guide breaks down what the percentiles actually mean, how Houston stacks up against peer metros, what drives the salary gap from P25 to P90, and the specific moves that shift offers.

What the Houston data scientist percentiles actually mean

The 2024 OEWS data for SOC 15-2051 in the Houston-Pasadena-The Woodlands MSA is sourced from BLS via O*NET and covers base wages only. No equity, no bonus, no LTI.

PercentileAnnual Base Wage
P25$80,250
P50 (Median)$100,420
P75$132,380
P90$164,300

The $84,000 gap between P25 and P90 is enormous for a single job title. It reflects the real-world reality that “data scientist” in Houston means at least four different things depending on employer: an analyst who builds dashboards and runs SQL queries for a midstream pipeline company, a classical statistician running predictive maintenance models at a refinery, a machine learning engineer building natural language processing pipelines at a health system, or a staff-level AI researcher at a major energy supermajor’s advanced analytics team. The BLS survey buckets all four into the same SOC code.

For practical purposes, treat the percentile ranges this way:

  • P25 ($80K) — entry-level to two years’ experience, analyst-flavored DS roles, smaller energy services companies, regional healthcare employers, and contract positions.
  • P50 ($100K) — mid-level generalist data scientists with three to six years of experience at mid-tier energy companies, hospital systems, or industrial analytics shops.
  • P75 ($132K) — senior DS at a major energy company or large healthcare system, or mid-level DS with strong ML skills at a tech-forward employer.
  • P90 ($164K) — principal or staff-level DS, specialized ML/AI engineers at supermajors, or DS leads at the handful of genuine software tech companies with Houston offices.

How Houston compares to other Texas metros and major hubs

Houston is the largest city in Texas by population but not by data science salary. That distinction belongs to Austin, where the BLS OEWS 2024 data shows a median of $122,440 — 22 percent above Houston’s median. Dallas-Fort Worth ($120,840 median) also runs ahead of Houston. San Antonio ($107,850) is closer. At the national level, the BLS May 2024 national median for SOC 15-2051 was $112,590.

MarketBLS 2024 DS MedianCOL Index
San Francisco~$180,000+178.6
Seattle~$155,000+142.0
New York City~$150,000+168.0
Austin, TX$122,440119.3
Dallas-Fort Worth$120,840103.0
National Median$112,590100.0
San Antonio$107,85091.0
Houston$100,42094.1

Houston’s lower median relative to Austin and Dallas is partly structural. Tech company density in Houston is lower; the biggest DS employers here are energy, healthcare, and financial services rather than the software-first companies that anchor Austin’s upper percentiles. But Houston’s COL index of 94.1 — meaning living costs run about 6 percent below the US average — changes the after-tax picture meaningfully. A $100K base in Houston has higher purchasing power than the national median suggests. COL-adjusted, it punches closer to $107K in real terms.

What drives the P25-to-P90 spread in Houston

The employer mix is everything. Houston’s data science labor market segments into four distinct tiers based on who you work for, and tier determines base range more than years of experience does.

Energy supermajors and advanced analytics divisions. ExxonMobil, Shell, bp, and Chevron’s Houston operations have invested heavily in data science and ML over the past five years — predictive maintenance, reservoir simulation, supply chain optimization, and increasingly, LLM-driven document intelligence for contracts and regulatory filings. ExxonMobil’s DS roles in Houston range from roughly $130K (mid-level) up to $210K+ at senior and staff levels per Levels.fyi data, with an average total compensation around $210K for the CL27 band. These employers pay base-heavy, offer defined-benefit or cash-balance pension components that other sectors have abandoned, and often include meaningful annual bonuses (10–15% of base). Equity is minimal or absent; the tradeoff is genuine long-term benefits. This tier anchors the P75–P90 range in the BLS data.

Large healthcare systems and medical centers. The Texas Medical Center — the world’s largest medical complex by number of institutions — has produced a significant DS hiring ecosystem. Houston Methodist, Memorial Hermann, MD Anderson, and UTHealth are active DS employers, but they pay below commercial rates. Levels.fyi shows Houston Methodist DS pay in the $53K–$101K range, well below the metro median. Academic medical center pay scales are compressed and bonus structures are limited. These roles sit at P25–P40 in the BLS data and are appropriate entry points for DS professionals interested in clinical informatics, but they’re not competitive against the energy sector.

Midstream, downstream, and energy services companies. Below the supermajors sits a large tier of DS employers: pipeline operators, LNG terminal analytics teams, oilfield services companies (Halliburton, Baker Hughes, SLB), and refining analytics groups. Compensation here typically runs $90K–$130K base for mid-level, with bonus programs that are real but smaller than the supermajors’. These companies are responsible for the P50 band in the BLS data.

Financial services, retail, and tech adjacents. Hewlett Packard Enterprise, Sysco, Aramco Americas, and a growing set of professional services firms with Houston analytics practices round out the market. Pay in this tier is generally in the $95K–$140K range for mid-level DS, with variable equity programs depending on whether the employer is publicly traded. Houston’s startup ecosystem is modest compared to Austin’s, so early-stage equity upside plays are rare here.

Specialty premium. Across all sectors, three skills currently command a meaningful premium over generalist DS work in Houston: machine learning operations (MLOps) at scale, large language model fine-tuning and evaluation, and geospatial data science applied to subsurface or pipeline operations. If your background includes any of these, expect offers at or above P75 regardless of years of experience.

Total compensation breakdown

Unlike Austin or San Francisco, Houston data science comp is heavily weighted toward base salary and annual cash bonus. Equity plays a secondary role at most employers here.

A representative mid-level DS offer at a major energy company or large industrial employer in Houston looks like:

  • Base salary: $100,420 (BLS median; real offers in this tier typically run $105K–$120K after company-specific adjustments)
  • Annual target bonus: ~$12,000 (10–12% of base is common at energy majors and healthcare systems; supermajors can reach 15–20% at senior levels)
  • Equity or LTI: ~$18,000 annualized (more variable; energy supermajors often substitute pension or ESPP for equity; tech-adjacent employers may grant RSUs closer to $25K–$40K annualized at mid-level)
  • Sign-on bonus: $5,000–$15,000, common for roles that require a move or specialized background

That puts representative total cash compensation at around $130K for a solid mid-level role, with total compensation (including LTI or ESPP equivalents) landing around $150K when benefits loading is factored in.

For senior and staff-level DS roles at energy supermajors — the P90 cohort — total compensation climbs substantially. ExxonMobil’s senior-level DS packages at their Houston AI and digital units routinely total $180K–$250K when base, bonus, and LTI are combined. The spread between the BLS P90 base figure and actual total comp at that level reflects how much of the compensation at supermajors is delivered through structured non-equity programs that BLS does not capture.

COL-adjusted purchasing power

Houston’s C2ER Cost of Living Index of 94.1 (Q4 2024 annual average) means everyday costs run about 6 percent below the US average. Housing is the largest driver: Houston’s housing costs run roughly 17–20 percent below the national average, which is exceptional for a metro of its size. Utilities run somewhat above average. Transportation and healthcare are near-national.

The practical effect: a $100K Houston data scientist salary has the purchasing power of approximately $106K at the national baseline. A $132K P75 offer is effectively $140K in national-average terms. This is the math that makes Houston look like better value than raw salary comparisons suggest.

Versus Austin: Austin’s $122,440 BLS median sounds 22 percent higher than Houston’s $100,420. But Austin’s COL index of 119.3 means living costs run 19 percent above the US average. Adjusted, Houston’s median is worth $106,400 in national-average dollars; Austin’s is worth $102,600. The gap essentially disappears on a cost-of-living-adjusted basis, and Houston has no state income tax either — the same Texas tax advantage Austin DS workers cite applies here.

Versus San Francisco: The COL-adjusted gap is stark in the other direction. SF’s BLS median for DS is roughly $180K+ on a COL index of 178.6. That translates to about $101K in national-average purchasing power — nearly identical to Houston’s adjusted $106K. The real differentiation in San Francisco is total comp, particularly equity, which BLS does not capture. For DS roles without meaningful equity upside — which describes the majority of energy and healthcare roles in both cities — Houston’s after-tax, after-COL position is genuinely competitive.

Three-lever negotiation playbook

Lever 1: Use the sector spread to your advantage. If you have genuine ML or AI skills (not just “I know Python and have built a few models”), you belong in the energy supermajor or energy-tech tier, not the healthcare or midstream tier. The base difference between these tiers for similar skills can be $25K–$40K. Before negotiating any offer number, establish which tier you’re dealing with. If a recruiter from a hospital system or energy services company gives you a P40-range offer, the counter is not “I want more money” — it’s “I’ve also been speaking with an energy major and their entry-level for this background is $X.” That reframes the market quickly.

Lever 2: Negotiate bonus structure, not just base. In Houston’s energy and industrial sector, annual bonus programs have real teeth — 10–20% of base is common and is paid in cash, not equity. Most candidates negotiate base and ignore bonus percentage. If an employer quotes you a 10% bonus target, asking about the conditions for 15% (strong individual + company performance) is a legitimate line of conversation. The difference between 10% and 15% on a $120K base is $6K per year — over five years, that compounds.

Lever 3: Anchor to P75 for senior roles, P50+10% for mid-level. The BLS P75 for Houston DS is $132,380. For any senior or specialist DS role, this is the minimum floor for a competitive offer. For mid-level generalist positions, a 10% premium over the $100,420 median — roughly $110K — is defensible and well within the range. Recruiters at major energy companies have access to the same OEWS data their HR compensation teams use; arriving with “the BLS 75th percentile for this role in Houston is $132K” is a grounded, non-confrontational anchor that signals preparation and removes the “you’re asking for above market” deflection.

Concretely: get three data points before any negotiation. (1) The BLS OEWS percentile for your experience level in Houston. (2) The Levels.fyi data for your specific employer and title, if available. (3) Any competing offer you have in hand. Two of those three is usually enough to move an offer.

Caveats with the data

BLS OEWS covers base wages only. The $100,420 median does not include bonus, equity, pension contributions, ESPP, or the generous defined-benefit pension programs that major energy companies still offer. For energy sector roles especially, stripping the comparison down to base salary understates total compensation at the top tier by 20–35%.

The May 2024 data reflects wages from 2024. AI/ML skill premiums accelerated through 2025, and the gap between generalist DS and specialist ML/LLM roles has widened. The P90 may already be running $170K–$185K in base for specialist roles by mid-2026.

SOC 15-2051 lumps junior through principal together. The BLS bucket includes everyone with the “data scientist” title, which creates a wide spread. If you are benchmarking a senior or staff role, weight the P75–P90 range, not the median. If you’re evaluating an entry-level offer, P25 is the right reference point.

Energy sector comp has structural non-base components. Pension, ESPP, and LTI programs at supermajors are harder to compare directly with equity-heavy tech offers. A $120K base with a 15% pension match and 15% bonus target has a different effective value than a $140K base with a 5% bonus and no pension. Model the full package, not just the salary line.

Houston Methodist and similar healthcare system salaries are outliers downward. Academic medical center pay for DS roles runs well below commercial rates in this metro. If a comparison or job aggregator includes these salaries in a “Houston DS average,” it will pull the number lower than the commercial market warrants.

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