Title: Google Cloud Platform Data Engineer Location: Remote (Preferably from Cleveland, OH) Duration: 6+ Months Summary Seeking a Google Cloud Data Engineer to join a talented team to build a new and exciting data produc…
Engineering & IT · Cleveland, OH
Data Scientist jobs in Cleveland, 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.
565
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$36–$88/hr
Typical pay range
$120k
Median, full-time
5
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Title: Agentic AI Engineer Location: Pittsburgh, PA, Dallas, TX OR Cleveland, OH Employment Type: Full Time Required qualifications to be successful in this role: Should be good in AI Agents automation development proces…
Lead AI Engineer Location Cleveland, OH (Onsite) Only GC / USC Job Summary Lead AI engineer, Hands on AI engineering and solutions delivery. GCP and kubernetes Node JS / Typescript micro services AI Patterns Lang Graph,…
Description POSITION SUMMARY Flexjet is seeking a detail-oriented AI Data Engineer to build and maintain data infrastructure that powers... ...and AI systems. In this role, you will work closely with data scientists, ML…
AI Engineer to design, develop, and deploy machine learning and artificial intelligence solutions. You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive…
Midwestern IT! We offer online training and placement opportunities through direct marketing, and we are currently hiring for Data Analyst and Business Analyst roles. Job Title: Business Analyst / Data Analyst Job Type:…
Job Description Job Description WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further. Further is a data, cloud, and AI company whose focus is h…
Job Description Job Description POSITION SUMMARY Flexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy enterprise-scale AI and Generative AI solutions that improve productivity, au…
Ensure compliance with responsible AI, security, risk management, data privacy, auditability, reproducibility, documentation, and... ...development, and performance accountability. · Partner with Data Scientists, Softwar…
Key Roles & Responsibilities Lead and oversee the end-to-end design, implementation, and optimization of data pipelines supporting key customer onboarding, transaction, and decisioning workflows. Architect and implement…
Job Description Job Description WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further. Further is a data, cloud, and AI company whose focus is h…
Job Description Job Description WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further. Further is a data, cloud, and AI company whose focus is h…
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What data scientists earn in Cleveland
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$49 | $74k–$101k |
| Mid level | $49–$66 | $101k–$138k |
| Senior | $64–$88 | $133k–$184k |
Adjusted for the Cleveland 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
01
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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