$96.96k - $145.44k
Technology, Applications DevelopmentCompany: CitiAre you a Java virtuoso who sees code as a craft? Do you thrive on transforming complex data into powerful, elegant backend solutions? We're looking for a Senior Java Deve…
Engineering & IT · Tampa, FL
Data Scientist jobs in Tampa, FL
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
543
Open roles today
$38–$95/hr
Typical pay range
$129k
Median, full-time
9
Fresh in this list
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01
Open data scientist roles
12 shown of 543 · sorted by freshness
What you'll be doing: Verizon’s Exposure and Vulnerability Management (EVM) Engineering and Reporting team is seeking a Sr. AI and Data Engineer to lead the development of our security data architecture, web infrastructu…
processes that minimize environmental impact and foster vibrant and diverse communities around the globe.Jabil is seeking a Senior Labor Data/ Reporting Analyst to work onsite in our St. Petersburg, FL location.How will…
$129.3k - $177.8k
engineering, and productionization of AI-enabled automation across the Data Governance organization. This role is focused on building... ...training foundational models or serving as a traditional data scientist. The eng…
business orientation and multitasking skills.Excellent analytical skills and attention to detail.Ability to interpret and summarize data. Ability to work collaboratively in a team environment.Strong communication, writte…
preparation, production, and coordination of written products and briefings for senior stakeholdersExperience with assessments, enterprise data integration, governance, and metrics, including the application of metadata…
frameworks like Django, Flask, FastAPI, or others depending on the specialization.Develop and integrate APIs for Gen AI orchestration and data analytics workflows.Integrate popular Large Language Models (LLMs) such as Op…
Have Technical/Functional Skills 1. Strong experience in Kafka, Spark, Scala,SQL ,Hive, Impala, Hadoop, Splunk, Autosys . 3. Data Analysis and Data Wrangling skills when dealing with Huge Volume. 4. Performance analysis,…
$87.5k - $131.1k
Fraud, or Marketing — within our Analytics & Insights team. In this role, you will own the full analytics lifecycle, from building data pipelines and writing structured SQL queries in AWS Redshift, to developing compelli…
$85.39k - $116.98k
Syms Strategic Group (SSG) is seeking a talented Senior Systems Engineer (Amazon Web Services (AWS) Data Engineer) - II Location: Remote Department: Veterans Affairs (VA) Type: Full Time Min. Experience: Experienced Secu…
$140k - $203k
one day. A member of our recruitment team will provide more details. Job Overview: MUFG is seeking a highly motivated Security Data Architect & Governance person to be part of the Program Governance team to drive the Sec…
$92k - $130k
the rental residential real estate business. To learn more, visit . JOB DESCRIPTION SUMMARY Greystar's D²AI organization ( Data, Digital, and AI) is responsible for the platforms, processes, and practices that power anal…
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What data scientists earn in Tampa
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$52 | $79k–$109k |
| Mid level | $52–$71 | $109k–$148k |
| Senior | $69–$95 | $144k–$198k |
Adjusted for the Tampa market from national ranges.
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What employers ask for
The skills these listings keep naming
Python (pandas, scikit-learn)SQLStatistics and A/B testingMachine learning fundamentalsData visualizationExperiment designCommunicating with stakeholdersDomain and product sense
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through a data project that changed a decision.
Structure it as question, approach, finding, action. Projects that ended in a decision — even 'we did not launch' — beat technically impressive analyses that went nowhere.
How would you design an A/B test for a new feature?
Cover the metric, randomization unit, sample size, and duration, plus a pitfall like peeking or interference. Practical rigor is what is being tested.
Your model performs well offline but poorly in production. Why might that be?
Discuss train/serve skew, data leakage, distribution shift, and feedback loops. Listing several plausible causes and how you would check each is the strong answer.
Explain p-values or confidence intervals to a non-technical stakeholder.
Use plain language and a concrete scenario, and resist overstating certainty. They are testing whether your statistics survive translation.
How do you handle missing or messy data?
First ask why it is missing — the mechanism matters more than the imputation method. Then discuss options and how the choice affects conclusions.
When would you not use machine learning for a problem?
When a rule, a query, or a simple heuristic wins on cost and interpretability. Knowing when ML is overkill signals maturity.
How do you decide which metric a team should optimize?
Talk about proxy versus true goals, gameability, and counter-metrics. A story about a metric that backfired is very effective here.
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Resume tips that move the needle
For data scientists specifically — generic advice costs you here
01
Lead every bullet with the business result — revenue, retention, cost — and put the method second.
02
Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
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Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
04
Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
05
Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
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Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
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