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Data Science Product Manager Jobs in Ohio (NOW HIRING)

Alined Consulting Group

Product Manager

Columbus, OH · On-site

Required 3+ years of Product Management experience delivering software products. Demonstrated ... Bachelor's degree in Business, Information Systems, Computer Science, Data Analytics, or a related ...

Socket.dev

Data Science & Analytics Specialist

Bath, OH · On-site

$90 - $130/hr

Overview Apogee Engineering has a exciting position for a Data Science & Analytics Specialist that ... Familiarity with basic data management and data quality concepts. Preferred Qualifications:

New

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Lead Data Science Projects * Translate complex business requirements into robust, scalable ... Ensure solutions are production ready, maintainable, and aligned with MLOps best practices. * Drive ...

GRVTY

Data Science - Senior

Dayton, OH

Build and manage datasets for training and evaluation in collaboration with subject matter experts ... Advanced degree in Computer Science, Data Science, Electrical Engineering, or related field, or ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Lead Data Science Projects * Translate complex business requirements into robust, scalable ... Ensure solutions are production ready, maintainable, and aligned with MLOps best practices. * Drive ...

VTG

Data Scientist

Beavercreek, OH

Provide technical input to program managers and government representatives Do you have what it takes? Required qualifications: * Bachelor's Degree, majoring in majoring in Computer Science, Data ...

84.51°

Lead Data Engineer (P4519)

Cincinnati, OH · On-site

$125K - $207K/yr

Communication and Collaboration with Product and Data science are critical to success and are ... Bachelor's degree typically in Computer Science, Management Information Systems, Mathematics ...

Munich Re

Data Scientist

Cleveland, OH · On-site +1

We write admitted products in all 50 states and have a premium volume of $2.2 billion ... Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments ...

Munich Re

Data Scientist

Cincinnati, OH · On-site +1

We write admitted products in all 50 states and have a premium volume of $2.2 billion ... Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments ...

Munich Re

Data Scientist

Akron, OH · On-site +1

We write admitted products in all 50 states and have a premium volume of $2.2 billion ... Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments ...

Munich Re

Data Scientist

Amelia, OH · On-site

We write admitted products in all 50 states and have a premium volume of $2.2 billion ... Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments ...

Munich Re

Data Scientist

Dayton, OH · On-site +1

We write admitted products in all 50 states and have a premium volume of $2.2 billion ... Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments ...

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All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Ohio

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 22, 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.

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.

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.

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:

Data Science Product Manager jobs near you
Infographic showing various Data Science Product Manager job openings in Ohio as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $151,546 per year, or $72.9 per hour.

BN31M1-Manager, Scientific AI Engineering & Data Science

Chemical Abstracts Service

Columbus, OH • On-site, Remote

Full-time

Posted 5 days ago

Job description

Position Overview
The Manager, Scientific AI Engineering & Data Science is a people-leadership role. The manager builds, grows, and leads a team of data scientists and AI engineers who develop the systems behind CAS's scientific discovery products - the retrieval, extraction, and reasoning that power CAS Newton℠ and CAS Connections, and internal platforms. The role sits in the Data Analytics & Insights (DAI) organization.
The manager's primary work is people: hiring, coaching, developing, and retaining data scientists and AI engineers, and creating the conditions for the team to do its best work. Technical direction, architecture, and roadmap delivery are owned by technical leads and product partners. The manager is expected to carry enough technical fluency to lead, coach, and mentor credibly - to understand the work, judge the quality of an engineer's contributions, and guide growth - but is not accountable for owning the technical roadmap or shipping it.
The role is not bounded by the manager's own set of direct reports. As DAI scales and elevates aggressively, the manager brings team-wide and enterprise-wide thinking to the role and steps in to drive cross-cutting initiatives as priorities dictate. The ideal candidate can speak fluently and confidently about the team's work to both internal and external audiences.
People Leadership & Talent
  • Own hiring for a growing team - sourcing, recruiting, interviewing, and evaluating talent.
  • Develop, retain, and motivate data scientists and AI engineers with scientific domain depth; shape and build the team.
  • Coach and mentor across levels, supporting both technical growth and career progression.
  • Manage performance and career development in line with the DAI career framework - job family, scope tier, and depth/breadth path.
  • Build bench strength, support succession, and sustain a healthy, inclusive, high-expectation team culture.
  • Match people to work thoughtfully, balancing team delivery with individual growth and job satisfaction.
Technical Fluency & Coaching
  • Maintain enough fluency across modern AI engineering - LLMs, agentic workflows and tool use, RAG, retrieval and extraction over scientific content, and evaluation - to lead and coach the team credibly.
  • Judge the quality of the team's technical work well enough to give meaningful feedback and guide development.
  • Understand the trustworthy-AI principles the team works to - including CAS's reliance on curated, provenanced scientific content, and the difference between acceptable model variability and genuine failure - well enough to reinforce them.
  • Partner with technical leads and product, who own technical direction, architecture, and roadmap.
Team Health & Enablement
  • Ensure the team is well-resourced, unblocked, and set up to succeed, working with technical leads and product on prioritization and staffing.
  • Remove organizational and people-level obstacles, and escalate and resolve issues that slow the team.
  • Support healthy operating practices - delivery rhythm, review, and production health - without owning roadmap outcomes.
Team-Wide Leadership & Enterprise Mindset
  • Bring team-wide and enterprise-wide thinking to the role, in service of scaling and elevating the organization aggressively.
  • Step in to lead and drive cross-cutting initiatives as priorities dictate - for example, specific programs with internal partners or targeted team-elevation efforts - unconstrained by the manager's own set of direct reports.
  • Speak fluently and confidently about the team's work to both internal and external audiences, including customers, partners, and the broader scientific community.
  • Approach the role with an ownership mindset that extends beyond the immediate team to the broader organization's success.
Partnership & Communication
  • Partner across Product, Technology, Content Operations, and other teams as the people leader for the team.
  • Represent the team's capacity, needs, and health to stakeholders and leadership.
  • Connect the team's people and capabilities to CAS's broader goals.
Qualifications
Education
  • Master's degree in a relevant technical or quantitative discipline (e.g., Computer Science, Applied Mathematics, Statistics, Data Science, Computational Chemistry, Physics, Bioinformatics), or equivalent experience.
  • A PhD and/or deep scientific domain expertise (chemistry, life sciences, materials science) is valued as a capability the person brings, and is not required.

Experience
  • 8+ years of relevant experience, including 3-5+ years developing people and leading technical teams.
  • Enough hands-on background in AI/ML engineering and data science to lead and coach the work credibly; direct roadmap or delivery ownership is not required at this level.
  • Familiarity with modern AI engineering - LLM-based, agentic, and large-scale retrieval and extraction systems.
  • Experience in scientific, chemical, pharmaceutical, or materials-science domains is desired.

Leadership & Competencies
  • Proven ability to hire, coach, grow, and retain technical talent.
  • Strong people-management, feedback, and career-development skills.
  • Team-wide and enterprise-wide perspective, and readiness to lead initiatives beyond one's own reporting line.
  • Ability to represent the team's work fluently and confidently to internal and external audiences.
  • Sound judgment on team health, culture, and prioritization.
  • Sufficient technical fluency to earn the trust of a team of data scientists and AI engineers.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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