Position Overview We are seeking an experienced Data Engineer III to design, develop, and maintain modern enterprise data platforms supporting business intelligence and analytics initiatives. This role focuses on buildin…
Engineering & IT · Cincinnati, OH
Data Scientist jobs in Cincinnati, 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.
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$36–$89/hr
Typical pay range
$121k
Median, full-time
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powered by intelligent machines. If you're driven by ambition, success, fun, and learning, Nexaminds is where you belong. As a Data Testing Engineer , you will be the Quality subject-matter expert on a dedicated Scrum Te…
$55 - $70 per hour
Location: Cincinnati, Ohio Duration: Contract Job ID: 178780 Job Overview: We are seeking a highly skilled and experienced Senior Data Engineer to design, develop, and support scalable IBM DataStage ETL solutions and ent…
Job Description Job Description For more than three decades, Strategic Data Systems (SDS) has been a software consultancy firm specializing in strategy, technology, and business transformation for Fortune 100 companies,…
Job Summary We are seeking an experienced Data Scientist to drive causal inference, experimentation, measurement, personalization, and applied AI initiatives. The ideal candidate will have hands-on experience applying ca…
Our corporate activities are growing rapidly, and we are currently seeking a full-time, office-based Junior Data Engineer to join our Information Technology team. This position will work on a team to accomplish tasks and…
Greetings, We’re looking for a senior-level Data Engineer with expertise in DBT, Snowflake, and SQL to design and deliver scalable data solutions in a high-impact banking environment. Data Architect / Principal Data Engi…
Job Title: Data Engineer IV Location: Cincinnati, OH - onsite Payrate $70/hr on W2. USC and GC Holder candidates only.... ...robust data infrastructure. You'll work closely with data scientists and ML engineers to delive…
Job Description Job Description Description: On Site in Cincinnati, Ohio Our client seeks a Data Engineer/Architect III to assess and optimize Cloudera NiFi implementations, strengthen ETL and ELT pipelines, and enable r…
Job Description Job Description Sr. Data Engineer for Cincinnati OH Will work on the projects from inception to end using Azure cloud technologies like PySpark, Spark SQL, Azure Data Lake Storage, Azure Data Factory, Azu…
Description Job Description For more than three decades, Strategic Data Systems (SDS) has been a software consultancy firm specializing... ...members of your team (eg, data architects, the IT team, data scientists) on th…
Job Description Job Description ComResource is looking for a Data Engineer. We need someone to assist in calculating FDIC insurance... ...systems. Collaborate with data architects, IT, and data scientists to achieve proj…
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What data scientists earn in Cincinnati
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$49 | $74k–$102k |
| Mid level | $49–$67 | $102k–$140k |
| Senior | $65–$89 | $135k–$186k |
Adjusted for the Cincinnati 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
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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
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Lead every bullet with the business result — revenue, retention, cost — and put the method second.
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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
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Junior Data Scientist
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Data Scientist
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Senior Data Scientist
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Staff Data Scientist
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Head of Data Science
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