$140k - $160k
Manager of Data Engineering Overview A leading enterprise organization is seeking a Manager, Data Engineering to lead a team responsible for delivering modern data solutions that support Finance and Supply Chain business…
Engineering & IT · Columbus, OH
Data Scientist jobs in Columbus, OH
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
1,943
Open roles today
$37–$91/hr
Typical pay range
$124k
Median, full-time
7
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01
Open data scientist roles
12 shown of 1,943 · sorted by freshness
of a global team of over 50,000 planners, designers, engineers, scientists, digital innovators, program and construction managers and... ...Description AECOM is seeking a Senior Electrical Engineer, Data Center specializ…
of a global team of over 50,000 planners, designers, engineers, scientists, digital innovators, program and construction managers and... ...seeking to hire a highly skilled Mechanical Engineer for the Data Center and Mis…
$105.5k - $175.9k
Requirements: Bachelors degree in Computer Science, Information Systems, or a related field Minimum of 4 years of relevant experience in data engineering, analytics engineering, or modern data platforms Proficient in clo…
$108.8k - $181.3k
Requirements: We require a BA/BS degree or equivalent experience in data analytics, business, public health, or a related discipline;... ...affordable. Our CoverMyMeds team is hiring a Strategic Data Scientist to help re…
Role: Senior Data Engineer/Data Engineer Location: Columbus, OH Duration: 6 Months Job Description Technology Stack Reference: Development activities will primarily leverage Snowflake, Matillion, AWS Services (S3, Lambda…
; } tr th { background-color: #f5f5f5; } Job Title Lead Data Engineer (Senior Programmer/Analyst) Location Columbus, OH... ...successful candidate will work closely with business stakeholders, data scientists, analysts,…
PhD trained modeler and data scientist Contract Location - New York & Columbus Skill - AI/ML
Learning Centers and training locations in the United States, Canada, France and the United Kingdom. Purpose of Position The Lead Data Engineer is a hands-on technical leader responsible for architecting, developing, and…
bout the job you're considering As the organization continues to expand its data ecosystem across cloud and on-premise platforms, there is a growing need to establish strong data governance, transparency, and trust in en…
Data Testing-SQL Designs and executes comprehensive data quality testing strategies for ETL, Big Data, and data-intensive applications, including BAO, MDM, and data migrations. Develops a deep understanding of business r…
Data Engineer Full Time Columbus, OH About Andhealth AndHealth is a healthcare technology company created to radically improve access and outcomes for the most challenging chronic health conditions. We are driven by the…
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What data scientists earn in Columbus
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$50 | $76k–$104k |
| Mid level | $50–$68 | $104k–$142k |
| Senior | $66–$91 | $138k–$190k |
Adjusted for the Columbus 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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