Is Data, Analytics & AI a Good Job Market in Austin-Round Rock-San Marcos, TX?

Executive Verdict

Market rating: competitive | Confidence: High

Austin is still a viable but selective market for Data, Analytics & AI. Local postings over the last 90 days totaled more than 250 across more than 150 companies, but the mix skewed about 45% mid-level and about 40% senior while Austin's Information sector was down -3.0% year-over-year in March 2026.[21][6][14] Texas-specific field data tells the same story: Revelio Public Labor Statistics shows Data, Analytics & AI employment down 2.1% year-over-year in Texas even as active postings rose 5.3% in April 2026.[22][23] That points to a market with real openings, but tighter screening and more competition for each role.

Best positioned: The best odds right now belong to mid-career or senior candidates who can pair Python and SQL with business-facing analytics or applied ML, because local postings most often request Python and SQL and skew toward experienced hiring.[8][6]

Main caution: The biggest mistake is assuming Austin's AI buzz means abundant remote junior roles; about 55% of sampled openings are on-site, only about 15% are entry-level, and recent Meta, Oracle, and Expedia cuts can add experienced competition.[7][6][10][11][12]

What Changed Recently

• Texas field-level signals got more selective: Revelio Public Labor Statistics shows Data, Analytics & AI employment in Texas down 2.1% year-over-year in April 2026 even as active postings rose 5.3%.[22][23]: That usually means employers are still opening roles, but filling them more cautiously and with tighter skill screens.
• Austin's local sector backdrop split in two in March 2026: Information employment fell -3.0% year-over-year while Professional and Business Services grew 1.7%.[14][17]: Analytics work tied to business operations, consulting, client service, or internal decision support looks safer than openings tied only to pure tech expansion.
• Local risk rose with a Meta WARN notice published on 2026-04-23 affecting 8,000 employees for May 20, 2026, alongside Oracle layoffs beginning in April 2026 and an Expedia Group notice affecting 100 employees in April 2026.[10][11][12]: Even when cuts are not all data roles, they raise the odds that experienced tech workers re-enter the same Austin hiring pool.
• The national macro picture is cooler than the AI narrative suggests: CPI was up 3.1% year-over-year in March 2026, average hourly earnings rose 3.6% year-over-year in April 2026, and national unemployment sat at 4.3% in April 2026.[24][25][26]: For Austin job seekers, that means compensation still matters, but employers have less reason to rush hires or overpay for generalists.

What This Means for You

Entry-Level Candidates

Difficulty: Hard locally because only about 15% of sampled openings are entry-level and the typical active posting has been open around 25 days, which means junior applicants need sharper proof of skill than a generic resume provides.[6][32]

Best target: Target analyst roles that combine Python, SQL, and data visualization in business functions such as healthcare, real estate operations, or internal reporting rather than pure AI-research branding.[8][20][18]

Biggest mistake: Applying as a generalist without a portfolio that shows one real workflow from messy data to dashboard to business recommendation.

Next step: Build two tightly scoped case studies in the next month: one SQL/Python analysis and one dashboard project with a short memo explaining the decision impact.

Mid-Career Candidates

Difficulty: Moderate but competitive because about 45% of openings are mid-level, posted pay centers on about $120k to $171k, and the market is spread across more than 150 employers rather than a few obvious buyers.[6][1][21]

Best target: Aim at business-facing analytics, decision support, and applied ML roles where Python, SQL, machine learning, and stakeholder communication travel well across industries.[8][18]

Biggest mistake: Leading with tools alone instead of showing how your work changed revenue, cost, risk, or operations.

Next step: Rewrite your resume around quantified outcomes and split your search into two lanes: business analytics roles and applied AI roles.

Career Switchers

Difficulty: Hard unless you bring domain credibility, because Austin openings skew toward mid and senior hires and only about 10% of postings that state a sponsorship policy mention visa sponsorship being available.[6][16]

Best target: The cleanest path is domain-to-analytics: finance to FP&A analytics, operations to business operations analytics, or healthcare operations to reporting and forecasting work.

Biggest mistake: Trying to jump straight into AI engineer titles without first proving analytics fundamentals and domain context.

Next step: Package your prior domain wins into one analytics narrative, then pursue adjacent analyst roles before stretching to data scientist titles.

Salary Reality

high pay highly concentrated

Observed local posted ranges center on about $120k to $171k, with a broader 25th-75th band of about $90k to $215k.[1] Separate proxy Austin data-scientist estimates place pay around $79,350 at the 25th percentile, $121,630 on average, and $138,280 at the 75th percentile.[2][3] At the broader state level, Revelio Public Labor Statistics puts the mean offered salary on new Texas openings in this category at about $114,322 in April 2026 (n=8,111), which is directional rather than a metro median.[4]

Austin can still pay well for data talent, especially once you clear the junior band, but that upside sits in a metro where salaries and cost of living remain above the national average.[5]

The tradeoff is access: only about 15% of sampled openings are entry-level, about 40% are senior, and about 55% are on-site, so higher pay often comes with stricter experience screens and less location flexibility.[6][7]

Best-paying path: The strongest pay tends to sit in mid-to-senior roles that combine machine learning or AI work with production-grade workflows, especially when Python, SQL, PyTorch, and domain context come together.[8][9]

Caution: Do not overread top-end salary figures: the highest posted bands are likely pulled up by specialist or leadership openings, while salary aggregators cover only slices of the category and not every Austin sub-role equally.[1][2][3]

Where the Opportunities Are Concentrated

Real opportunity is concentrated less in one employer and more in a few industry clusters. In the local sample, technology and information technology each account for about 35% of Data, Analytics & AI postings, with smaller but real demand in healthcare, financial services, and computer hardware development at about 5% each.[18] Over the last 90 days, we observed more than 250 postings across more than 150 companies, and hiring was fragmented rather than dominated by one brand.[21][15] That matters because Austin is not behaving like a one-company market. The recurring employers in the sample include RevOps Advisor, Migrate Mate, Apple, Advanced Micro Devices, Inc., Future Secure AI Pty, and IntegraFEC.[19] There are also domain-specific analytics openings outside classic software, such as CBRE's Senior Energy & Utility Data Analyst supporting a healthcare portfolio across Austin and Round Rock and asking for Tableau, Smartsheet, and 2-5 years of relevant experience.[20] For most job seekers, the best odds are in roles that solve an operating problem inside a business function—forecasting, reporting, experimentation, efficiency, or model-enabled decision support—rather than in pure research-style AI titles.

• Tech and applied AI (high): Technology and information technology each represent about 35% of the local posting mix, and the recurring names in the sample include Apple, Advanced Micro Devices, Inc., and Future Secure AI Pty.[18][19]
• Business and revenue operations analytics (high): Hiring is fragmented across many employers, and RevOps Advisor is one of the most consistently active names in the local sample, which supports a practical lane into reporting, funnel analysis, and business decision support.[15][19]
• Healthcare and facilities analytics (moderate): Healthcare accounts for about 5% of the local category mix, and CBRE is hiring an Austin-area Senior Energy & Utility Data Analyst tied to a healthcare portfolio, showing demand for domain-specific analytics outside consumer tech.[18][20]
• Financial services analytics (moderate): Financial services is only about 5% of the local sample, so it is not the dominant lane, but it remains a credible alternative for candidates with risk, forecasting, or KPI experience.[18]

Where to focus: Focus on mid-to-senior roles where you can show a full analytics workflow and a clear business outcome, especially in business operations, applied AI, healthcare operations, or hardware-adjacent analytics.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 60% of local postings, making it the clearest baseline filter skill in this market.[8]
• SQL (table stakes): SQL shows up in about 40% of local postings, which means even AI-branded roles still expect comfort with structured data and business reporting logic.[8]
• Machine learning and PyTorch (premium): Machine learning appears in about 25% of local postings and PyTorch in about 15%, while national skill signals show growing demand for deep learning, NLP, and transformer-related work.[8][9]
• Data visualization and dashboarding (differentiator): Data visualization appears in about 15% of local postings, and a current Austin-area CBRE role explicitly asks for Tableau and dashboard work tied to operational decision-making.[8][20]
• MLOps and cloud workflow (premium): National signals show MLOps, data engineering, and cloud skills such as AWS, Azure, GCP, Docker, Kubernetes, and CI/CD are in demand as data teams move toward production-grade model pipelines.[9]
• Responsible AI and data governance (differentiator): Responsible AI and data governance are moving from nice-to-have to operational requirement as employers embed AI into real decisions.[27]
• Google Professional Machine Learning Engineer or CAIP (differentiator): Local postings rarely make certifications mandatory, with machine learning certification mentioned in less than 5% of the sample, but advanced AI credentials such as Google Professional Machine Learning Engineer and CAIP can still help signal seriousness for premium ML tracks.[28][29]

Adjacent Roles to Consider

• Business Operations Analyst (bridge): Austin's Professional and Business Services sector grew 1.7% year-over-year in March 2026, and many local analytics openings sit inside operational business functions rather than pure platform teams.[17][18]
• Revenue Operations Analyst (both): RevOps Advisor is one of the most consistently active local employers in the current sample, which signals real overlap between analytics skills and revenue-operations work.[19]
• FP&A Analyst / Financial Analyst (pivot): Financial services accounts for about 5% of the local category mix, giving analytically strong candidates a credible adjacent lane if they can add finance fluency.[18]
• Energy or Sustainability Analyst (both): CBRE's Austin-area Senior Energy & Utility Data Analyst role shows that analytics skills can transfer into facilities, utilities, and sustainability work tied to healthcare operations.[20]

30 / 60 / 90-Day Plan

First 30 Days

• Split your resume into two versions: one for business analytics and one for applied AI or ML.
• Build one Austin-relevant case study that combines SQL extraction, Python analysis, and a dashboard with a one-page business memo.
• Create a target list of 40 local employers across tech, IT, healthcare, finance, and hardware-adjacent firms, then tag each by on-site, hybrid, or remote fit.
• Apply only to roles posted within the past week and customize your first five bullets to the exact problem in the job description.

Days 31-60

• Ship a second portfolio piece focused on a domain problem such as forecasting, anomaly detection, experiment analysis, or operational efficiency.
• Practice three interview stories that each show a measurable outcome: cost saved, revenue lifted, risk reduced, or time cut.
• Add one workflow upgrade that changes your screening odds, such as stronger Tableau work, better SQL depth, or a basic cloud deployment demo.
• Start a referral loop from former managers, clients, classmates, and domain peers instead of relying only on cold applications.

Days 61-90

• If direct data-scientist traction is weak, widen your title set to senior analyst, business operations analyst, revenue operations analyst, or domain-specific analyst roles.
• Expand your search radius to hybrid roles in the broader Austin-Round Rock corridor and be explicit about commute flexibility.
• Publish your best project in recruiter-friendly form: GitHub repo, slide deck, dashboard screenshots, and a short case brief.
• Review every rejection pattern and reposition around the lane where you get interviews, not the title that sounds most prestigious.

Methodology and Confidence

This April 2026 report was generated on May 10, 2026. Latest direct national data: May 2026. Latest direct Austin-Round Rock-San Marcos, TX data: April 2026.

Confidence: Overall confidence: High. Based on 6 direct local occupation data points and 27 total local evidence items with recent coverage.

Limitations

• Austin's most detailed federal occupation benchmark for this broader field lags current conditions, so fast changes in AI and analytics hiring may show up first in sector data, layoff notices, and recent postings rather than in occupation counts.
• Some statewide Data, Analytics & AI signals were used as a proxy because metro-level monthly occupation series are not published at the same detail, so Austin can be stronger or weaker than the Texas average.
• The Callings.ai job database is a partial, deduplicated sample of online postings, so direction of demand, leading employer names, seniority mix, and skill patterns are more reliable than exact counts or exact market shares.
• Several recent government year-over-year figures are preliminary and may be revised, which matters when you are reading small changes in employment or sector growth.
• Recent layoff notices identify real employer-level risk in the metro, but they do not show how many affected workers were specifically in data, analytics, or AI roles.

References

1. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
2. Agentsforhire. Agents for Hire · 2026-02 · agentsforhire.ai
3. Usawage. Data Scientist Salary in Austin-Round Rock-San Marcos, Texas · 2026-04 · usawage.com
4. Reveliolabs. Salaries - Revelio Public Labor Statistics (RPLS) · 2026-04 · reveliolabs.com
5. Gusto. Average Salary in Austin, TX - April 2026 | Gusto · 2026-04 · gusto.com
6. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
7. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
8. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
9. Refontelearning. Refonte Learning : Data Science & AI in 2026: Top Trends, Essential Skills, and Career Strategies · 2026-02 · refontelearning.com
10. Twc. Texas Workforce Commission · 2026-04 · twc.texas.gov
11. Statesman. Oracle layoffs reported as AI spending ramps up · 2026-03 · statesman.com
12. Cbsaustin. Austinites lose tech jobs as companies re-focus on AI development · 2026-02 · cbsaustin.com
13. Reveliolabs. Mass-layoff Notices - Revelio Public Labor Statistics (RPLS) · 2026-04 · reveliolabs.com
14. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-03 · data.bls.gov
15. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
16. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
17. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-03 · data.bls.gov
18. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
19. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
20. Careers. Careers - senior_energy_analyst_hiring · 2026-04 · careers.cbre.com
21. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
22. Reveliolabs. Employment - Revelio Public Labor Statistics (RPLS) · 2026-04 · reveliolabs.com
23. Reveliolabs. Job Openings - Revelio Public Labor Statistics (RPLS) · 2026-04 · reveliolabs.com
24. Federal Reserve Economic Data. Consumer Price Index for All Urban Consumers: All Items in U.S. City Average · 2026-03 · fred.stlouisfed.org
25. Federal Reserve Economic Data. Average Hourly Earnings of All Employees, Total Private · 2026-04 · fred.stlouisfed.org
26. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.bls.gov
27. Analytics8. AI and Data Strategy in 2026: What Data Leaders Must Get Right · 2026-01 · analytics8.com
28. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
29. Ucertify. AI Certifications 2026: Top 10 Powerful Certifications to Boost Your Career · 2026-04 · ucertify.com
30. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai
31. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.bls.gov
32. Callings.ai. Callings.ai job-market aggregation · 2026-04 · callings.ai