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Data Science Product Manager Jobs (NOW HIRING)

Ecolab

Sr Data Scientist

Saint Paul, MN · On-site

$118K - $177K/yr

Drive experimentation and delivery of digital AI / data science product innovations aligned to the ... Experience in consulting and/or product management * Well-developed and proven leadership ...

Ecolab

Sr Data Scientist

Naperville, IL · On-site

$118K - $177K/yr

Drive experimentation and delivery of digital AI / data science product innovations aligned to the ... Experience in consulting and/or product management * Well-developed and proven leadership ...

Harley-Davidson

Mgr Data Science

Milwaukee, WI

Auto req ID: 52054 Title: Mgr Data Science Job Function: Digital Location: JUNEAU Workplace ... Review performance of implemented plans and models as well as the effect of data science products ...

Epitec

Data Product Manager

Dearborn, MI · On-site

$67 - $70.97/hr

Data Product Manager Location: Hybrid: 4 days onsite, 1 day remote in Dearborn, MI Job Type: W2 ... The ideal candidate will bridge business, engineering, analytics, and data science teams to deliver ...

BranchLab

Manager of Data Science

Boulder, CO · On-site

$160K - $215K/yr

THE OPPORTUNITY We are seeking a Data Science Manager to lead a team of data scientists and drive ... The ideal candidate will have experience developing and deploying models into production ...

Definitive Healthcare, US

Data Scientist

Framingham, MA

$92K - $172K/yr

This role is ideal for someone who thrives at the intersection of data science, product innovation ... Lead strategic product enhancements , including defining project plans, managing timelines, and ...

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All JobsData Science Product Manager Jobs

Data Science Product Manager information

See salary details

$51.5K

$159.4K

$197K

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

As of Jun 8, 2026, the average yearly pay for data science product manager in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 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 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.
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Data Science Product Manager jobs near you
Infographic showing various Data Science Product Manager job openings in the United States as of May 2026, with employment types broken down into 62% Full Time, 35% Part Time, and 3% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Data Scientist/ Product Analytics

TECHOAUTH SOLUTIONS LLC

Fort Worth, TX • Remote

$123K - $174K/yr

Full-time

Posted yesterday

Job description

Job: Data Scientist/ Product Analytics
Location: Remote
Employment Type: Full-Time
About the Role
We are looking for a Data Scientist who will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation. This person will partner closely with product, engineering, design, and business stakeholders to identify opportunities, define success metrics, analyze user behavior, and turn data into practical recommendations.
This role is ideal for a senior individual contributor who enjoys ambiguous problems, can move quickly in a startup environment, and can balance hands-on execution with strategic guidance.
What You Will Do
Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention
Define and maintain clear metrics that help the company understand product health, customer behavior, and business performance.
Design, analyze, and interpret experiments and quasi-experiments to guide product and investment decisions.
Build dashboards, recurring reporting, and lightweight self-serve tools that help product and business teams answer common questions faster.
Create reliable datasets and partner with engineering to improve event tracking, data quality, and analytical foundations.
Translate complex analyses into clear narratives, recommendations, and tradeoffs for technical and non-technical audiences.
Partner cross-functionally with product, engineering, design, marketing, and leadership to ensure insights are used in decision-making.
Mentor other analysts or data scientists as the team grows, and help establish strong practices for metrics, experimentation, and analytical review.
What We Are Looking For
6+ years of experience in data science, product analytics, applied statistics, or a closely related role. More senior experience is welcome.
Strong SQL skills and experience working with relational databases, event data, and product usage data.
Hands-on experience with Python or R for analysis, modeling, experimentation, and data visualization.
Experience defining metrics, building dashboards, and developing analytical frameworks that support product and business decisions.
Strong understanding of experimentation, A/B testing, causal inference, and common statistical methods used in product decision-making.
Ability to work independently in ambiguous environments and turn broad business questions into structured analysis plans.
Strong communication skills, including the ability to explain findings clearly to executives, product managers, engineers, and non-technical stakeholders.
A practical, startup-oriented mindset with strong ownership, urgency, and a bias toward action.

Preferred Qualifications

Advanced degree in Statistics, Mathematics, Economics, Computer Science, Operations Research, Physics, or a related quantitative field.
Experience in consumer products, marketplaces, social platforms, growth, or another data-rich product environment.
Experience creating analytical roadmaps, leading cross-functional measurement strategy, or advising senior leadership.
Experience building or improving data pipelines, semantic layers, experimentation platforms, or product analytics infrastructure.
Experience mentoring analysts or data scientists and raising the quality of analytical work across a team.

Compensation and Benefits
Competitive salary, based on experience, role scope, location, and applicable legal requirements.

This is a remote position.