Is Data, Analytics & AI a Good Job Market in Tampa-St. Petersburg-Clearwater, FL?

Executive Verdict

Market rating: competitive | Confidence: Medium

This is a workable market, but not an easy one. Tampa's broader labor market softened in May 2026, with metro unemployment at 4.5%, up 25.0000% year over year, while metro employment slipped 0.9885% year over year.[20][21] At the same time, Florida's Data, Analytics & AI market is holding up better than the general backdrop: Revelio Public Labor Statistics shows statewide employment in the field essentially flat year over year, but active postings up 14.5% year over year in June 2026, and the local sample still shows more than 100 postings across more than 50 companies over the last 90 days.[19][18][22] The catch is that local demand skews mid-to-senior and mostly on-site or hybrid, so this market favors candidates who can already deliver with Python, SQL, dashboards, and business-facing analytics in sectors like finance, healthcare, government, and professional services.[4][5][6][7]

Best positioned: Your best odds right now are as a mid-career analyst, BI, or data science candidate who can show Python, SQL, and dashboard work, and who is open to enterprise employers in financial services, consulting, healthcare, or government-heavy teams.[3][7][6]

Main caution: The biggest mistake is assuming Tampa is a remote-first or entry-level-friendly data market; only about 15% of sampled roles were entry level and only about 5% were remote.[4][5]

What Changed Recently

• Florida's Data, Analytics & AI postings are up 14.5% year over year in June 2026 even though statewide employment in the field is essentially flat.[18][19]: That usually points to more replacement hiring, backfills, and selective new requisitions than to broad headcount expansion, so you may see openings without a fast offer cycle.
• Tampa's metro unemployment reached 4.5% in May 2026, up 25.0000% year over year, while metro employment fell 0.9885% year over year.[20][21]: Even good analytics candidates are searching in a softer local economy, which raises competition and makes employer selectivity more noticeable.
• Local opportunity is spread across more than 50 companies rather than one dominant buyer, with recent activity led by Deloitte, Citi, and KPMG-related entities.[22][1][2]: You should run a broad, sector-specific search instead of building your plan around one marquee employer.
• Remote availability is limited locally: about 60% of sampled roles were on-site, about 35% hybrid, and about 5% remote.[5]: Candidates who insist on remote-only work are choosing from a much smaller slice of the Tampa market.
• Nationally, JOLTS openings rose to 7594 thousand in May 2026, up 3.8851% year over year, but hires were down 2.9655% and quits were down 6.7539%.[23][24][25]: There are still openings, but employers are filling them more cautiously, which fits a slower interview-to-offer environment for data and analytics roles.

What This Means for You

Entry-Level Candidates

Difficulty: Harder than average. The local mix is seniority-heavy, with only about 15% of sampled roles at entry level.[4]

Best target: Aim first at analyst, reporting, or BI-leaning roles in finance, healthcare, or public-sector teams that ask for Python, SQL, visualization, and dashboard work rather than pure research-heavy AI credentials.[7][6][8]

Biggest mistake: Applying only to remote data scientist titles or leading with coursework instead of work samples.

Next step: Build a four-piece proof set in the next month: one SQL project, one Python analysis, one Power BI or Tableau dashboard, and one short business memo that explains the decision behind the numbers.[8][6]

Mid-Career Candidates

Difficulty: Moderate. The market is selective, but it lines up better with your experience because about 40% of sampled roles are mid-level and about 40% are senior.[4]

Best target: Target enterprise analytics roles in financial services, consulting, healthcare, and government-facing teams, especially where Python, SQL, machine learning, and stakeholder reporting all show up together.[3][7][6]

Biggest mistake: Presenting yourself as a generic analyst when the local market rewards domain fluency and business translation.

Next step: Split your search into two lanes: business-facing analytics and advanced analytics. Tailor each resume to the sector problem you solve, not just the tools you know.

Career Switchers

Difficulty: Moderate to hard. Tampa offers real opportunity, but employers still signal bachelor's-level expectations in most postings that name education requirements.[17]

Best target: Switch through adjacent reporting, operations, finance, or compliance-heavy roles that still use SQL, dashboards, and structured analysis, then move deeper into the core data track after local experience.[7][6]

Biggest mistake: Trying to skip straight into ML-heavy titles without proving business reporting, data cleaning, and stakeholder communication.

Next step: Use a starter credential plus a local-sector portfolio: a Google Data Analytics Certificate or IBM Data Analyst Professional Certificate paired with Tampa-relevant projects in banking, healthcare, or public performance reporting.[9][10][7]

Salary Reality

high pay highly concentrated

The cleanest local wage anchor is the BLS median annual wage for data scientists in the Tampa metro at $109,990 for May 2025.[14] That is a direct government observation for one occupation. Fresher but broader signals show Tampa-area posted salary ranges for the category centering on about $105k to $173k, while Revelio Public Labor Statistics places Florida's mean offered salary on new openings for Data, Analytics & AI at about $110,557 in June 2026 (n=2,308).[15][35]

That combination points to good pay for qualified candidates and a clear premium over Florida's mean offered salary across all occupations of about $71,314, but it does not mean every data-role opening is a six-figure analyst job.[35]

The pay upside comes with a higher bar. Only about 15% of sampled local roles were entry level, while about 40% were mid-level, about 40% were senior, and only about 5% were remote.[4][5]

Best-paying path: The strongest pay tends to sit in enterprise roles, which account for about 65% of the local sample, especially in financial services and consulting-heavy employers and in roles that combine AI, machine learning, cloud, and business decision support.[3][7][36]

Caution: Do not overread the top of the posted ranges. The local posting band blends analyst, BI, data science, and AI-leaning jobs, while the direct local BLS wage is for data scientists only and lags current postings by about a year.[15][14]

Where the Opportunities Are Concentrated

Real opportunity in Tampa is concentrated less in a startup-style long shot market and more in recurring enterprise demand. The recent local sample shows more than 100 postings across more than 50 companies, with hiring fragmented rather than dominated by one firm, and recent activity led by Deloitte, Citi, KPMG-related entities, Bank of America, LTM, and ManTech.[22][1][2] About 65% of postings in the sample came from enterprise employers, which usually means clearer job scopes, more domain requirements, and slower hiring cycles than a small-company market.[3] The sector mix matters. Financial services accounts for about 20% of sampled postings, while government and public sector, technology, healthcare, and professional services each contribute about 15%.[7] The skill pattern matches that mix: python appears in about 70% of local postings, sql in about 40%, machine learning in about 30%, and data visualization in about 20%, with a separate June 2026 Tampa role explicitly emphasizing Power BI dashboards and reporting.[6][8] In practice, that means the safest bet is business-facing analytics, reporting, risk, and decision-support work before niche AI titles with thin local volume.

• Enterprise finance and consulting analytics (high): This is the clearest local lane, supported by financial services at about 20% of the sample and by active employers such as Deloitte, Citi, Bank of America, and KPMG-related entities.[7][1]
• Healthcare and public-sector reporting (moderate): Healthcare and government/public sector each account for about 15% of sampled demand, which supports dashboard, reporting, and KPI-driven analyst roles more than pure research-oriented AI work.[7][8]
• ML and cloud-enabled analytics (moderate): Machine learning appears in about 30% of local postings, AWS in about 15%, and AWS ML Specialty is the most frequently named certification at about 5%, so specialization helps but is not the whole market.[6][12]

Where to focus: Prioritize enterprise finance, consulting, healthcare, and public-sector analytics roles that ask for Python, SQL, dashboards, and stakeholder reporting, then use AI or ML specialization as an accelerator rather than your only pitch.[3][7][6][8]

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 70% of sampled local postings, making it the clearest baseline technical signal in this market.[6]
• SQL (table stakes): SQL shows up in about 40% of local postings and remains the common language across reporting, analytics, and decision-support roles.[6]
• Power BI and dashboard building (differentiator): A June 2026 Tampa role from Robert Half specifically emphasized turning complex data into dashboards and reports, reinforcing that reporting fluency still sells locally.[8]
• Machine learning plus AI literacy (premium): Machine learning appears in about 30% of local postings, and nationally 45% of data and analytics postings now mention AI-related skills, while AI literacy is increasingly treated as table stakes.[6][11][26]
• AWS and AWS ML Specialty (premium): AWS appears in about 15% of local postings, and AWS ML Specialty is the most frequently named certification in the local sample at about 5%.[6][12]
• Tableau and data visualization (differentiator): Data visualization appears in about 20% of local postings and Tableau in about 15%, which makes storytelling with metrics a practical edge in business-facing teams.[6]
• Google Data Analytics Certificate or IBM Data Analyst Professional Certificate (differentiator): Both credentials are designed for entry-level preparation and cover the practical stack employers still ask for, including SQL, Python, analytics basics, and reporting tools.[9][10]
• Finance and regulatory domain fluency (premium): Financial services is the largest single industry slice in the local sample at about 20%, and finance leaders nationally continue to pay more for specialized data analytics skills.[7][27]

Adjacent Roles to Consider

• Financial analyst / FP&A analyst (both): Tampa's local demand leans toward financial services and enterprise employers, including Citi, Bank of America, Deloitte, and KPMG-related entities, so candidates who can turn data work into budgeting, forecasting, and performance analysis widen their target list.[1][7]
• Risk or fraud analyst (pivot): The finance-heavy local employer mix supports analytic work tied to controls, fraud detection, and risk scoring, especially for enterprise teams.[1][7]
• Operations analyst / business operations (bridge): Healthcare, government/public sector, and professional services each represent about 15% of the local sample, and these teams often hire metric-driven operators before they hire fully specialized data talent.[7]
• Compliance or reporting analyst (bridge): Local demand includes strong reporting and dashboard work, and Tampa's healthcare plus public-sector footprint makes compliance-oriented analysis a practical side door into the market.[8][7]

30 / 60 / 90-Day Plan

First 30 Days

• Rebuild your resume into two versions: one for business analytics and reporting, one for advanced analytics and AI. Local demand spans both, with heavy asks for Python, SQL, visualization, and some machine learning.[6]
• Create one finance KPI dashboard and one healthcare or public-sector reporting sample, because those sectors make up a large share of the local opportunity mix.[7][8]
• Broaden your search filters to on-site and hybrid immediately; about 60% of sampled roles are on-site and about 35% are hybrid, versus about 5% remote.[5]
• Make a named employer list led by Deloitte, Citi, KPMG-related entities, Bank of America, and similar enterprise firms, then look for referrals before applying cold.[1]

Days 31-60

• If you are entry-level or switching, complete a starter credential such as the Google Data Analytics Certificate or IBM Data Analyst Professional Certificate, then attach it to real SQL and Python work samples.[9][10]
• If you are already experienced, add an AI layer to your portfolio: prompt-assisted analysis, an ML example, or AWS ML Specialty prep. AI-related skills now appear in 45% of data and analytics postings nationally, and AWS shows up locally.[11][6][12]
• Follow up earlier than you think. The typical active local posting has been open around 48 days, which suggests slower close cycles and more room for organized follow-up.[13]
• Practice business translation in interviews. Enterprise employers make up about 65% of the local sample, so decision-making and communication matter alongside technical depth.[3]

Days 61-90

• If response rates stay weak, pivot some applications into adjacent finance, risk, operations, or compliance roles that use the same SQL and dashboard stack and sit inside Tampa's strongest sectors.[1][7][8]
• Add one domain proof project tailored to a local employer type: bank risk dashboard, consulting KPI pack, public performance report, or healthcare utilization view.[1][7]
• Use both the BLS local data scientist wage and the current local posting range as salary anchors, but calibrate expectations by seniority because entry-level representation is limited.[14][15][4]
• If you need visa sponsorship, screen early and aggressively; among local postings that explicitly stated a policy, about 0% mentioned sponsorship availability.[16]

Methodology and Confidence

This June 2026 report was generated on July 10, 2026. Latest direct national data: July 2026. Latest direct Tampa-St. Petersburg-Clearwater, FL data: July 2026.

Confidence: Overall confidence: Medium. The local wage anchor is solid, but several conclusions about hiring shape and sub-role demand rely on broader category and posting-pattern evidence.

Limitations

• The freshest direct metro wage anchor in this report is the BLS data scientist wage for May 2025, so it does not fully capture the newest salary movement in mid-2026 AI and analytics titles.[14]
• Several local labor-market changes used here, including the May 2026 unemployment and employment year-over-year moves for Tampa and Florida, are preliminary and may be revised later.[20][31][21][32][33][34]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so leading employer names, skill patterns, seniority mix, and work-arrangement trends are more reliable than exact counts or exact market shares.[22][1][5][4][6]
• Statewide Data, Analytics & AI figures from Revelio Public Labor Statistics were used as a proxy for hiring direction because comparable metro-by-occupation readings are not published here; that means the direction-of-hiring signal is Florida-wide, not Tampa-only.[19][18]
• Salary signals combine a direct local government wage for data scientists with broader category posting ranges and statewide offered-salary estimates, so they should be read as boundaries for different sub-roles rather than one expected salary for every analyst, BI, or AI job.[14][15][35]

References

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7. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
8. Robert Half. Power BI Data Programmer Analyst Job in Tampa, FL · 2026-06 · roberthalf.com
9. Forbes. Forbes - new_certification_google_data_analytics · 2026-07 · forbes.com
10. Coursera. 7 Popular Data Analytics Certifications: Your 2026 Guide · 2025-12 · coursera.org
11. Pulsjob. AI Skills Employers Want in 2026: Essentia... · 2026-06 · pulsjob.com
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13. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
14. Bureau of Labor Statistics. May 2025 OEWS Metropolitan and Nonmetropolitan Area Definitions · 2026-05 · bls.gov
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20. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
21. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
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23. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
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26. Unojobs. AI Skills Every Job Seeker Needs in 2026 | UnoJobs · 2026-03 · unojobs.com
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29. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
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31. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
32. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
33. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
34. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
35. Reveliolabs. Salaries - Revelio Public Labor Statistics (RPLS) · 2026-06 · reveliolabs.com
36. Robert Half. 2026 Technology salary trends: The skills and roles driving growth · 2025-09 · roberthalf.com