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

Executive Verdict

Market rating: competitive | Confidence: High

Austin is a good-paying market for Data, Analytics & AI, but it is a selective one rather than an easy one. Local Data Scientist wages center at $122,440, and sampled posted salary ranges across the broader category center on about $124k to $184k.[1][2] At the same time, the metro unemployment rate was 4.1% in June 2026 and up 17.1429% year over year, while the sampled role mix was about 10% entry, 45% mid, 35% senior, and 5% lead+.[23][6] Statewide, Revelio Public Labor Statistics shows Texas Data, Analytics & AI employment down 0.8% year over year even as active postings rose 28.5% year over year in July 2026, which points to active recruiting but selective hiring.[19][20]

Best positioned: Your best odds are as a mid-career or senior candidate who can prove Python and SQL fluency, plus a differentiator in machine learning, Tableau/BI, AWS, or governance, and who is open to hybrid or on-site work.[11][7][10]

Main caution: The biggest trap is assuming Austin's pay upside means broad access: only about 10% of sampled openings were entry level, about 15% were remote, and less than 5% of postings that stated a policy mentioned visa sponsorship.[6][7][8]

What Changed Recently

• Texas Data, Analytics & AI postings rose 28.5% year over year in July 2026 while statewide employment in the category fell 0.8% year over year, according to Revelio Public Labor Statistics.[20][19]: That mix usually means more openings to apply to, but tighter matching and slower fill decisions than a pure expansion cycle.
• Austin's labor force grew 0.8321% year over year in June 2026, but employment grew only 0.1921% and unemployment reached 4.1%, up 17.1429% year over year.[21][22][23]: More people are looking than last year, so generic applications are easier to ignore.
• The local job mix remained office-linked: about 45% of sampled roles were on-site, about 45% hybrid, and about 15% remote, with the typical active posting open around 34 days.[7][24]: If you hold out only for remote roles, you shrink your reachable market and likely lengthen the search.
• National hiring conditions are steady, not hot: U.S. nonfarm payrolls were 158,858 thousand in July 2026, up 0.1993% year over year, while the JOLTS openings rate was 4.4% versus a 3.4% hires rate in June 2026.[17][25][26]: Employers are still posting, but posting volume is not translating into especially fast hiring, so expect more screening rounds and slower movement.

What This Means for You

Entry-Level Candidates

Difficulty: Hard.

Best target: BI analyst, reporting analyst, or operations-facing analytics roles where you can prove data cleaning, SQL, dashboarding, and business communication before aiming at pure data scientist titles.

Biggest mistake: Applying to every AI or data scientist posting without a portfolio that shows business questions, metrics, and usable outputs.

Next step: Build one strong case study around a dashboard, KPI definition, and decision memo, then target hybrid Austin roles that ask for analytics execution rather than advanced research.

Mid-Career Candidates

Difficulty: Manageable if your recent work shows shipped outcomes.

Best target: Roles that combine Python, SQL, stakeholder ownership, and one domain edge such as operations, customer support, healthcare, finance, or governance.

Biggest mistake: Leading with tools only instead of showing how your work changed a forecast, process, SLA, cost line, or product decision.

Next step: Split your search into two tracks: operational analytics/BI and AI-enabled analytics, and tailor your resume examples to each path.

Career Switchers

Difficulty: Hard-to-moderate depending on how much domain credibility you bring.

Best target: Analytics roles adjacent to your current industry, especially where domain knowledge matters as much as deep modeling.

Biggest mistake: Trying to erase your prior background instead of using it as proof that you understand the operating context behind the data.

Next step: Repackage your prior work into analytics language: metrics owned, reporting built, process improvements made, and decisions influenced.

Salary Reality

good pay high barrier

Government wage data for local Data Scientists shows a median annual wage of $122,440, with a 25th percentile of $86,390 and a 75th percentile of $157,300.[1] For the broader Austin category, sampled posted salary ranges center on about $124k to $184k, while employee-reported Data Analyst total compensation on Levels.fyi centers at $138,000 with an average range of $108,000 to $165,700.[2][3]

Even allowing for different measurement methods, Austin data work pays well above the area's broad wage base: Austin computer and mathematical occupations averaged $56.16 an hour in May 2024 versus $34.32 across all occupations, and Texas new openings in this category averaged about $123,548 versus about $78,561 across all openings.[4][5]

The upside is offset by selectivity: only about 10% of sampled local roles were entry level, only about 15% were remote, and less than 5% of postings that stated a policy mentioned visa sponsorship.[6][7][8]

Best-paying path: The strongest pay appears in senior and company-specific paths such as upper-end analyst roles and AI-heavy teams; one live Austin Lead Data Analyst posting advertised $110,000 to $135,000, and Levels.fyi lists Meta as Austin's highest-paying named company for Data Analysts at $192,000 average total compensation.[9][3]

Caution: Do not read top-end figures as the market norm: government wages, posted salary ranges, and employee-reported total compensation are different measures, and the highest numbers often reflect seniority, equity, or a small set of employers.[1][2][3]

Where the Opportunities Are Concentrated

Real opportunity exists, but it is spread across a long tail of employers. Over the last 90 days, the sampled market showed more than 200 postings across more than 125 companies, and hiring was fragmented rather than dominated by a few firms.[31][13] The most-active industries in the local sample were technology and software development at about 20% each, followed by government & public sector at about 15%, then financial services and real estate at about 10% each.[32] The role mix is more practical than the category label suggests. Local signals show active needs in healthcare analytics leadership, business intelligence tied to real-time dashboards and capacity modeling, contact-center analytics, robotics-adjacent analytics, and consulting-style AI work focused on roadmaps, DataOps, cloud, and governance.[33][9][34][10] In other words, Austin is rewarding people who can connect data work to operations, service delivery, and domain problems more than people pitching themselves as generic AI generalists.

• Operational BI and telemetry analytics (high): Business intelligence openings emphasize real-time dashboards, capacity modeling, network performance, and contact-center analytics, including a Lead Data Analyst role paying $110,000 to $135,000.[9]
• Consulting and AI transformation (high): Austin listings include Data & AI consulting work around AI roadmaps, DataOps, AWS, governance, and workflow redesign, including a Principal AI Transformation Consultant signal.[10]
• Public sector and enterprise reporting (moderate): The local sample includes TX-HHSC-DSHS-DFPS and Texas Workforce Commission among active employers, and about 30% of postings come from enterprise employers.[35][14]
• Healthcare analytics leadership (moderate): Local postings also include senior healthcare analytics work applying advanced data science and machine learning to healthcare data, but that signal is senior-skewed rather than broad-based.[33]

Where to focus: Target roles where analytics is tied to an operating function—support operations, public programs, finance, healthcare, or revenue teams—because that is where Austin's demand looks most concrete.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 75% of sampled local postings, making it the clearest baseline filter.[11]
• SQL (table stakes): SQL appears in about 55% of sampled postings and is still the everyday language of reporting, experimentation, and data pulls.[11]
• Tableau / Power BI / data visualization (differentiator): Tableau appears in about 20% of sampled postings, data visualization in about 15%, and Austin BI listings emphasize real-time dashboards and business-facing reporting.[11][9]
• Machine learning plus AI literacy (premium): Machine learning appears in about 25% of sampled local postings, and national evidence shows AI-skilled workers earn a 56% wage premium while AI-skill requirements in job postings grew 144% year over year.[11][16]
• AWS, DataOps, and governance (differentiator): Austin AI and analytics listings increasingly combine cloud, DataOps, and governance rather than treating them as separate specialties.[10]
• Real-time dashboards and capacity modeling (differentiator): Local BI work is not just report building; employers are explicitly asking for real-time dashboards, capacity modeling, and performance insights.[9]
• Power BI Data Analyst Associate / Tableau Data Analyst / Data+ / CAP (differentiator): Credentials such as Microsoft Power BI Data Analyst Associate, Salesforce Tableau Data Analyst, CompTIA Data+, AWS Certified Data Engineer – Associate, and INFORMS CAP remain useful signaling devices when your work history is lighter than the role asks for.[12]
• LLM APIs, vector databases, and MLOps basics (premium): For AI-heavy paths, proficiency with LLM APIs, vector databases, and tools such as Docker, MLflow, and FastAPI is increasingly treated as baseline rather than bonus.[15]

Adjacent Roles to Consider

• Data Analytics Business Strategist (bridge): Austin listings include a Data Analytics Business Strategist role, which is a natural bridge for analysts who are strongest at stakeholder translation, KPI design, and decision support rather than deep modeling.[9]
• AI Transformation Consultant (pivot): Austin-area listings include a Principal AI Transformation Consultant role, showing demand for people who can redesign workflows, adoption plans, and governance around AI.[10]
• Data Product Manager (pivot): Data product manager is one of the emerging neighboring roles in 2026 as teams move from experiments to operational products.[15]
• AI Model Auditor (both): AI model auditor is emerging as organizations put more emphasis on model governance, risk checks, and human judgment around AI outputs.[15][16]

30 / 60 / 90-Day Plan

First 30 Days

• Rewrite your resume into two versions: one for BI/operations analytics and one for AI/ML/governance, because Austin openings are split between dashboard-heavy work and transformation-style Data & AI roles.[9][10]
• Build one portfolio case that includes SQL, Python, and a business-facing dashboard, then add a short write-up on how you handled data quality, definitions, and decisions.[11]
• Expand your target list to hybrid and on-site roles within commuting distance; about 90% of sampled openings are not fully remote.[7]
• If you need sponsorship, widen your search beyond Austin immediately because less than 5% of postings that state a policy mention sponsorship.[8]

Days 31-60

• Pick one differentiator and prove it with an artifact: Tableau/Power BI reporting, AWS/DataOps/governance, or a machine-learning workflow with evaluation and stakeholder translation.[11][9][10]
• Pursue one signaling credential that matches your lane, such as Power BI Data Analyst Associate, Tableau Data Analyst, CompTIA Data+, AWS Certified Data Engineer – Associate, or CAP.[12]
• Create a targeted employer list that mixes enterprise, consulting, and public-sector employers rather than only famous tech brands; the local employer base is fragmented, and about 30% of sampled roles come from enterprise companies.[13][14]
• Practice a 10-minute case interview around capacity modeling, service operations, or KPI redesign so you can show business impact instead of only tool familiarity.[9]

Days 61-90

• If interviews stall, broaden into adjacent titles such as Data Analytics Business Strategist, AI Transformation Consultant, or Data Product Manager instead of recycling the same data scientist applications.[9][10][15]
• Publish a second case study using AI-assisted analysis with guardrails, showing prompting, verification, and workflow integration rather than a generic chatbot demo.[16][15]
• Move up-market on seniority only after your artifacts look senior; the local mix is weighted to mid and senior roles, so your proof has to match the level you seek.[6]
• Treat every target company like a tailored sale: mirror the domain, KPIs, and operating problem in the first third of your resume and outreach.

Methodology and Confidence

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

Confidence: Overall confidence: High. This report combines recent local wage anchors, current metro labor-market context, and fresh local hiring and salary signals.

Limitations

• The strongest metro wage anchor here is local Data Scientist pay observed in January 2026, so it is recent but still lags the August 2026 posting and salary signals used to show current hiring behavior.[1]
• This category is broader than one job title; Austin's direct government wage data here is for Data Scientists, while the broader category also includes analysts, BI specialists, analytics engineers, ML roles, and operations research work that can pay differently.[1]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so direction of demand, leading employer names, and skill patterns are more dependable than exact posting counts, employer shares, or salary-share math for Austin.[31][35][2][11]
• Some compensation figures come from posted salary ranges or employee-reported total compensation sources, which are useful for market direction but are not directly comparable to government wage measures.[2][3][1]
• Statewide Revelio Public Labor Statistics was used as a proxy where metro-level occupation data is not published, and recent BLS local labor-force, employment, and unemployment readings may later be revised.[19][21][23][22]

References

1. Mynextmove. Local Salary Info for Data Scientists at My Next Move · 2026-08 · mynextmove.org
2. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
3. Levels. Data Analyst Salary in Austin, TX · 2026-08 · levels.fyi
4. Bureau of Labor Statistics. Austin-Round Rock-San Marcos, TX, Metropolitan Area Data Tables · 2025-03 · bls.gov
5. Reveliolabs. Salaries — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
6. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
7. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
8. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
9. Builtinaustin. Best Business Intelligence Jobs in Austin, TX 2026 | Built In Austin · 2026-08 · builtinaustin.com
10. Builtinaustin. Best AI Automation Jobs in Austin, TX 2026 | Built In Austin · 2026-08 · builtinaustin.com
11. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
12. Ucertify. Top Data Analytics Certifications to Advance Your Career in 2026 · 2026-06 · ucertify.com
13. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
14. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
15. Radleyjames. How has the data science career path changed in 2026? - Radley James · 2026-08 · radleyjames.com
16. Archieapp. Companies Returning to Office: RTO Tracker [June 2026] · 2026-07 · archieapp.co
17. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-07 · data.bls.gov
18. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.bls.gov
19. Reveliolabs. Employment — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
20. Reveliolabs. Job Openings — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
21. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
22. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
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24. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
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26. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
27. Statesman. Client Challenge · 2026-07 · statesman.com
28. Gamesindustry. GamesIndustry.biz · 2026-07 · gamesindustry.biz
29. Reveliolabs. Mass-layoff Notices — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
30. Youtube. Youtube - oracle_layoffs_austin_ai_impact · 2026-06 · youtube.com
31. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
32. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
33. Builtinaustin. Best Data & Analytics Jobs in Austin, TX 2026 | Built In Austin · 2026-08 · builtinaustin.com
34. Builtinaustin. Best Robotics Data & Analytics Jobs in Austin, TX 2026 | Built In Austin · 2026-08 · builtinaustin.com
35. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai

Live Openings in This Market

This report is published monthly; its companion page tracks the active Data, Analytics & AI openings in Austin-Round Rock-San Marcos, TX from the live Callings.ai job index. Browse current Data, Analytics & AI openings in Austin-Round Rock-San Marcos, TX.