$112k - $150k
building the next generation of analytics and AI-powered solutions for supply chain and commercial operations. We're looking for a Staff Data Engineer to design, build, and maintain production data pipelines that transfo…
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.
426
Open roles today
$36–$89/hr
Typical pay range
$121k
Median, full-time
6
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open data scientist roles
12 shown of 426 · sorted by freshness
manage, and optimize information and business processes. IT Services spans a wide range of activities, including software development, data management, Cloud services, IT security, technical support, access governance, i…
leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global de…
$110.7k - $218.3k
across personas such as Field Sales, KAM, MSLs, or Field Reimbursement ManagersExperience with adjacent Salesforce products such as Data Cloud, Experience Cloud, or MuleSoft based integrationsExperience delivering in a S…
$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…
Accenture's SAP Analytics practice, you will be a member of a delivery teams and focus on client engagements centered on SAP's modern data and analytics platform — including SAP Datasphere, SAP Analytics Cloud (SAC), and…
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…
$187.2k - $197.6k
in SQL, Python, and Power BI. We are looking for hands-on experience building solutions in Microsoft Fabric or similar enterprise data engineering platforms. We require proven experience with ETL/ELT pipeline development…
convert business requirements into visual based analytics Conduct analysis for mapping source inputs and assist in design strategy for data modeling Daily maintenance support of dashboards Minimum Qualifications: Bachelo…
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…
$90 per hour
job summary: The Data Engineer - Finance Systems & Analytics plays a critical strategic role bridging the gap between Finance and Information Technology. In this position, you will transform complex business data require…
$140k - $180k
We are seeking an Azure AKS Architect with strong expertise in Azure, Kubernetes, Docker, DevOps, and Manufacturing Execution Systems (MES). The role will focus on designing, developing, deploying, and supporting scalabl…
02
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.
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
Ten quiet minutes a day
Applying for data scientist jobs in Cincinnati?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.