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.

439
Open roles today
$36–$90/hr
Typical pay range
$122k
Median, full-time
9
Fresh in this list

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01

Open data scientist roles

12 shown of 439 · sorted by freshness

QA Analyst

Robert Half · Jacksonville, FL

We are looking for a QA Analyst to support software testing initiatives for a high-visibility enterprise program in Jacksonville, Florida. This role partners closely with development and program teams to ensure applicati…

Posted 2d ago
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Data Platform Engineer

Syms Strategic Group, LLC (SSG) · Jacksonville, FL · Full-time
$85.39k - $116.98k

Syms Strategic Group (SSG) is seeking a talented Data Platform Engineer Location: Remote Department: Veterans Affairs (VA) Type: Full Time Min. Experience: Experienced Security Clearance Level: Public Trust (MBI) Salary…

Posted 3d ago
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Electrical Engineer - Data Center

Arcadis · Jacksonville, FL
$80.46k - $142.72k

deliver more impact together.Role description:As an Electrical Engineer you will lead the electrical discipline of multiple concurrent data center projects through pursuit, proposal, design, and construction phases. You…

Posted 4d ago
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Client Quantitative Analyst I

Bank of America Corporation · Jacksonville, FL

within a Line of Business or business discipline. Key responsibilities include leveraging databases to acquire client and performance data, transforming extracted data into meaningful insights and trends, and delivering…

Posted 4d ago
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Senior Rail Facility Engineer/Architect

HDR · Jacksonville, FL

DescriptionAt HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas t…

Posted 4d ago
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Sr. Cloud Systems Engineer

Mindlance · Jacksonville, FL

activities • Manages problem or escalated tickets and tasks and out of cycle requests from systems/software owners • Collects and presents data for reporting and planning • Assists with developing tactical strategies, pr…

Posted 4d ago
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Project Architect- Justice

HDR · Jacksonville, FL

DescriptionAt HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas t…

Posted 4d ago
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Cloud Engineer

Robert Half · Jacksonville, FL

streamline administration and repeatable tasks.• Contribute to secure cloud operations by applying sound controls for access, compliance, data protection, and environment governance.• Deliver responsive internal support…

Posted 4d ago
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Remote Associate Data Engineer/Analyst

Software Guidance & Assistance · Jacksonville, FL · Full-time
$92k - $118k

We look for 3+ years of relevant professional experience. Alternatively, we consider 1.5 years of experience in an Associate Data Engineer role or in data analytics. We require experience with Posit/R. We require experie…

Posted 1w ago
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Sr Staff Data Scientist

GE Renewable Energy Power and Aviation · Jacksonville, FL · Full-time

Job Description Summary The Sr Staff Data Scientist will work individually and / or lead horizontal teams to develop AI / ML / advanced analytics solutions which bring demonstrable value to Unison (a GE Aerospace busines…

Posted 1w ago
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02

What data scientists earn in Jacksonville

Hourly first — that's how the offer arrives

ExperienceHourlyAnnual, 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.

03

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.

05

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.

03

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.

06

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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