care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been describ…
Engineering & IT · Jacksonville, FL
Data Scientist jobs in Jacksonville, 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.
526
Open roles today
$36–$90/hr
Typical pay range
$122k
Median, full-time
9
Fresh in this list
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Open data scientist roles
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experienced Systems Analyst / Business Systems Analyst with strong SQL and healthcare payer domain expertise to support enterprise data and analytics initiatives. The ideal candidate will possess deep knowledge of health…
$63k - $73k
and maintenance of recurring business reports. ESSENTIAL JOB FUNCTIONS & RESPONSIBILITIES: Support e-commerce sales teams with data, reporting, and ongoing analysis to identify and execute growth opportunities across key…
Join Our Team Quality Analyst Openings We're hiring Quality Analysts who are committed to delivering reliable, high-quality software and improving the end-user experience. Location: Pittsburgh, PA Job Type: W2 Contract R…
$156.83k
powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. Data Analyst, Technology Consulting - Data & Analytics (Data Architecture & Engineering) – Fi…
$90 per hour
Job Summary We are seeking a senior-level Data Engineer for an opportunity supporting enterprise People Data, HR analytics, and modern data architecture initiatives. This role is ideal for a data professional who enjoys…
Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, mana…
$92k - $118k
Build complex queries, SSIS jobs, and SSRS/Power BI reports Use the latest T-SQL features while working with large volumes of data Develop, program, and code technology solutions across the software development lifecycle…
$123k - $163k
Salary: $123,000 - 163,000 per year Requirements: Strong, practical experience working with Microsoft Azure Extensive experience with Terraform and infrastructure as code Strong background building and maintaining CI/CD…
performance of all quality management functions for the MCPP-PHIL Task Order by implementing the following: Collect and analyze data to make decisions that improve Marine Corps engineering equipment readiness, maintenanc…
$65k - $78k
exceptions, and coordinate timely resolution with the appropriate stakeholders Work with the Desk and operational partners to maintain data integrity within risk management, workflow, documentation, and reconciliation sy…
Sr. Data Cloud Engineer(s)(multiple positions) – Duties are using relational database systems, CI/CD pipeline, Kubernetes for application deployments, terraform IAC, Observability using Splunk, server-side GitHub REST AP…
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What data scientists earn in Jacksonville
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$50 | $75k–$103k |
| Mid level | $50–$68 | $103k–$141k |
| Senior | $65–$90 | $136k–$188k |
Adjusted for the Jacksonville 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.
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Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
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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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