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Data Science Product Manager Jobs in Ohio (NOW HIRING)

Ability to partner with product managers and stakeholders to translate business needs into science ... Bachelor's or Master's in Statistics, Data Science, Computer Science, Applied Math, Economics, or ...

Data Science Tutor

Cincinnati, OH · Remote

$18 - $40/hr

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Data Science Tutor

Cleveland, OH · Remote

$18 - $40/hr

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Data Science Tutor

Columbus, OH · Remote

$18 - $40/hr

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Kemper's products and services are making a real difference to our customers, who have unique and ... Manages a small team of data scientists and data engineers to research, design, develop, deploy ...

The AI & Mobile Product Manager will own the product lifecycle from concept through adoption ... Daily Activities: • Collaborate with engineering, data science, and design teams to review ...

Bachelor's degree in Computer Science, Information Systems, Business, or a related field. * Experience in Product Management, Data Product Management, or related roles. * Strong experience with ...

Bachelor's degree in Computer Science, Information Systems, Business, Engineering, or a related field. * 8+ years of Product Management, Business Analysis, or Data Product Management experience.

New

Credence has an immediate need for a Data Science Manager at the journeyman level to support HQ AFMC A4/10 at Wright Patterson AFB, OH. . This role is ideal for a data professional who enjoys ...

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Data Science Product Manager information

See Ohio salary details

$49K

$151.5K

$187.3K

How much do data science product manager jobs pay per year?

As of Aug 2, 2026, the average yearly pay for data science product manager in Ohio is $151,546.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,000.00 and $187,300.00 per year, depending on experience, location, and employer.

What is a Data Science Product Manager?

A Data Science Product Manager is a professional who bridges the gap between data science teams and business objectives by guiding the development of data-driven products. They work closely with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure successful product delivery. Their role involves understanding both the technical aspects of machine learning and analytics as well as user needs and business strategy. This ensures that data-powered products are effective, user-focused, and aligned with organizational goals.

What is the hottest job of the 21st century?

Data Science Product Managers are among the most in-demand roles in the 21st century, combining skills in data analysis, product development, and strategic planning. They oversee data-driven products and require knowledge of tools like SQL, Python, and machine learning, often working in fast-paced tech environments. The role is expected to grow as organizations increasingly rely on data to make decisions.

Is 40 too late for data science?

A Data Science Product Manager can enter the field at age 40, as experience, domain knowledge, and skills like programming and statistical analysis are highly valued. Many professionals transition into data science roles later in their careers, and continuous learning through certifications or courses can facilitate this shift. Age is less important than relevant skills and experience in the data science industry.

Can data scientists make $300k?

Data science product managers and senior data scientists with extensive experience, specialized skills, and working in high-cost-of-living areas can earn salaries of $300,000 or more. Achieving this level often requires advanced knowledge of machine learning, strong business acumen, and leadership responsibilities, along with experience at top companies or in executive roles.

What are the key skills and qualifications needed to thrive as a Data Science Product Manager, and why are they important?

To thrive as a Data Science Product Manager, you need a strong background in product management, data analytics, and a foundational understanding of machine learning, often supported by a degree in a technical or quantitative field. Familiarity with tools like SQL, Python, JIRA, and knowledge of data platforms and agile methodologies is typically required. Excellent communication, strategic thinking, and the ability to bridge technical and non-technical teams are vital soft skills. These competencies ensure successful product development, effective stakeholder alignment, and the delivery of impactful data-driven solutions.

What is the difference between Data Science Product Manager vs Data Analyst?

AspectData Science Product ManagerData Analyst
Required credentialsBackground in data science, product management, or related fields; often requires experience with machine learning and data-driven product developmentTypically holds a degree in statistics, mathematics, or business; skills in data visualization and basic analytics
Work environmentCollaborates with product teams, data scientists, engineers; focuses on developing data products and strategiesWorks with business units to interpret data, generate reports, and support decision-making
Employer and industry usageUsed in tech companies, e-commerce, and organizations developing data-driven productsCommon across finance, marketing, healthcare, and business intelligence roles

The main difference is that Data Science Product Managers oversee the development of data products and strategies, requiring a blend of product management and data science skills. Data Analysts focus on interpreting data and generating insights to support business decisions. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

How does a Data Science Product Manager typically collaborate with data scientists and engineers during a product lifecycle?

A Data Science Product Manager plays a crucial role in bridging the gap between business objectives and technical teams. Throughout the product lifecycle, they work closely with data scientists to define project goals, prioritize features, and translate business needs into actionable data-driven solutions. They also coordinate with engineers to ensure the seamless integration of machine learning models into products, address technical constraints, and facilitate communication between cross-functional teams. This collaborative approach ensures that data science initiatives are both technically feasible and aligned with overall business strategy.

Can a data scientist be a product manager?

A data scientist can transition to a product manager role, especially if they develop skills in project management, user experience, and business strategy. While the roles have different focuses—data scientists analyze data and product managers oversee product development—both require strong communication and cross-functional collaboration. Experience with tools like A/B testing, roadmapping, and stakeholder management can facilitate this transition.
What are popular job titles related to Data Science Product Manager jobs in Ohio? For Data Science Product Manager jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Science Product Manager jobs in Ohio look for? The top searched job categories for Data Science Product Manager jobs in Ohio are:
What cities in Ohio are hiring for Data Science Product Manager jobs? Cities in Ohio with the most Data Science Product Manager job openings:
Infographic showing various Data Science Product Manager job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $151,546 per year, or $72.9 per hour.

15787 Data Scientist II

Smart Data

Cincinnati, OH • On-site

Contractor

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


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, mid-sized firms, and startups. At SDS, we empower our development teams to address our clients’ critical business challenges by leveraging cutting edge technologies. If you seek a workplace where your contributions are truly appreciated, then SDS is the company for you. Join us today to work alongside fellow development specialists and become a crucial part of our dynamic and cohesive community.

Job Title: Data Scientist

Location: Cincinnati, OH [onsite, downtown] OR Chicago, IL [Downtown, with travel to Cincinnati]

Years of Experience: 3+

CONTRACT TO HIRE - MUST BE ABLE TO CONVERT TO FTE W/O SPONSORSHIP***



TOP SKILLS:

  • Causal Inferences Experience
  • AI – Not a dealbreaker if they do not have a ton of experience, but must be willing to learn
  • Econ Metrics
  • Measurement processes
  • Quantify treatments back to business (How does purchasing behavior change with different treatments) 

 

What You’ll Do

 SUMMARY

We're seeking a Data Scientist to help shape the future of our AI and science capabilities. This is a senior individual contributor role for a technically strong, forward-thinking data scientist who can advance our Gen AI and causal ML capabilities, lead end-to-end development of scalable science solutions, and partner with product and cross-functional teams to drive vision and strategy in our space.


QUALIFICATIONS, SKILLS & EXPERIENCE

  • 3+ years of applied data science experience, with demonstrated progression in scope and technical complexity
  • Hands-on experience with Generative AI applications, including one or more of: LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development
  • Familiarity with causal ML and/or causal inference methods (e.g., CATE, heterogeneous treatment effect modeling, DiD, matching)
  • Strong proficiency in Python, SQL, and Git
  • Experience with Azure and Databricks, or comparable cloud-based data science platforms
  • Experience contributing to production-quality ML systems using software engineering best practices
  • Ability to partner with product managers and stakeholders to translate business needs into science solutions and roadmap priorities
  • Strong oral and written communication skills, with the ability to translate between technical and business audiences
  • Comfort with ambiguity—able to operate effectively in evolving problem spaces and contribute to early-stage vision and strategy
  • Bachelor's or Master's in Statistics, Data Science, Computer Science, Applied Math, Economics, or related quantitative field

 

Preferred:

  • Experience with MLOps practices including workflow orchestration, model monitoring, reproducibility, and deployment
  • Experience in retail, CPG, media, or marketplace analytics
  • Demonstrated ability to informally mentor or coach peers in technical best practices
  • Familiarity with experimentation frameworks and measurement pipelines



RESPONSIBILITIES

  • Advance our AI capabilities by designing, developing, and deploying Gen AI solutions—including LLM fine-tuning, prompt engineering, RAG pipelines, agentic workflows, and integration of Gen AI into existing measurement and science workflows.
  • Lead end-to-end development and scaling of data science solutions, from research and experimentation through productionization, ensuring solutions are robust, reproducible, and maintainable.
  • Partner with product managers and cross-functional stakeholders to shape the vision, roadmap, and prioritization of science products and capabilities in the personalization and loyalty space.
  • Contribute to the vision and early development of a holistic science layer—working to connect and consolidate scattered science capabilities into a unified, scalable framework.
  • Apply and extend causal ML and econometric methods (e.g., CATE, DiD, matching, panel methods) to support measurement, experimentation, and personalization at scale.
  • Build, maintain, and improve production ML and experimentation pipelines using sound MLOps and software engineering practices, including CI/CD, version control, testing, and documentation.
  • Research and evaluate emerging AI/ML technologies and methodologies, identifying opportunities to bring state-of-the-art approaches into production.
  • Serve as a technical leader and subject matter expert on the team, providing guidance and informal mentorship to peers and evolving into a formal mentor as junior talent joins the team.
  • Communicate complex technical findings and methodologies clearly to both technical and non-technical audiences, including leadership and product stakeholders.



 

What You’ll Get

SDS, Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.

  • Competitive base salary
  • Medical, dental, and vision insurance coverage
  • Optional life and disability insurance provided
  • 401(k) with a company match and optional profit sharing
  • Paid vacation time
  • Paid Bench time
  • Training allowance offering
  • You’ll be eligible to earn referral bonuses!