$50k - $70k
planning and investment management activities Prepare client meeting materials, reports, and presentations Analyze financial data and assist in developing personalized financial strategies Support portfolio reviews and i…
Engineering & IT · Louisville, KY
Data Scientist jobs in Louisville, KY
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
453
Open roles today
$35–$88/hr
Typical pay range
$118k
Median, full-time
7
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01
Open data scientist roles
12 shown of 453 · sorted by freshness
causes and recommend long-term solutions to improve system stability and reduce ticket volume · Support application integrations and data flow between systems, ensuring accurate and reliable information exchange · Assist…
testing, debugging & installing to support organization's distributed computer applications using IBM Datastage, MS SQL Server, DB2, Data Warehousing, and Snowflake; take lead role in dealing with users in defining new s…
career wherever you want it to go. Join EY and help to build a better working world. Ethics and Compliance Investigations Team – Data, Time & Expense Senior Associate At EY, you will have the chance to build a career as…
Accessibility Business Analyst Jefferson County Clerk's OfficeLouisville, KY Apply JOB SUMMARY The Accessibility Business Analyst supports the IT Project Manager in planning and carrying out the Clerk's Office digital ac…
$40.86 per hour
job summary: We are seeking a skilled Clinical Applications Analyst to join our team in supporting, upgrading, and implementing critical clinical applications and Electronic Medical Record (EMR) systems. This role plays…
IDR is seeking a Clinical Applications Analyst to join one of our top clients for an in-office opportunity in Louisville, Kentucky. This role involves supporting clinical applications with a primary focus on WellSky Reha…
$43 per hour
Required Skills and Experience: Minimum of 3 years of experience in business operations or related field Demonstrated expertise in data analysis and reporting Strong communication and presentation skills Experience worki…
$22.43 per hour
Legal Assistant (Management Analyst I) Position Description As a Legal Assistant (Management Analyst I), you will support the DOJ's Executive Office for Immigration Review, specifically supporting the Louisville KY, Immi…
Description Job Description Overview The Human Resources Information Systems Analyst is responsible for supporting operational data needs in our HR applications including ADP Enterprise, Cornerstone, iCIMS and any future…
stakeholders to deliver high-quality integrations and applications, providing technical expertise, and ensuring the highest standards of data integrity and security. Responsibilities Integration Development: Design, deve…
$172k - $237k
workflows at enterprise scale. Drive the engineering of high-quality data, feature, and evaluation pipelines that support reliable and continuously improving AI behavior. Partner with data scientists, platform engineers,…
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What data scientists earn in Louisville
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $35–$48 | $73k–$100k |
| Mid level | $48–$65 | $100k–$136k |
| Senior | $63–$88 | $132k–$182k |
Adjusted for the Louisville 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
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Staff Data Scientist
05
Head of Data Science
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