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Data Science Product Manager Jobs in Michigan (NOW HIRING)

Stellantis

Data Scientist

Auburn Hills, MI · On-site

Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar ...

Ford Motor Company

Data Product Manager

Dearborn, MI

As the Product Manager for Data Access, Privacy, and Governance , you will serve as the critical ... Requires a bachelor's or foreign equivalent degree in computer science, information technology or a ...

Ford Motor Company

Data Product Manager

Dearborn, MI · On-site

As the Product Manager for Data Access, Privacy, and Governance , you will serve as the critical ... Requires a bachelor's or foreign equivalent degree in computer science, information technology or a ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

... science products that power commercial recommendations while promoting data science best practices, actionable outputs and a high bar for model quality and reliability.  Data scientists work ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

Work closely with the Product Manager and Product Owner to translate Business Value needs into ... Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research ...

FastTek

Data Architect Specialist

Dearborn, MI · On-site

$58.50 - $75.25/hr

Bachelor's degree in Computer Science, Information Systems, Engineering, Business, Data Analytics, or a related field. * 5+ years of Product Management, Data Management, Business Intelligence ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

... science products that power commercial recommendations while promoting data science best practices, actionable outputs and a high bar for model quality and reliability.  Data scientists work ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar ...

Motorsport Hackers

Data Product Manager

Dearborn, MI · On-site

$120 - $150/hr

Join us and use your product management expertise and technical acumen to drive secure, scalable, and compliant data outcomes at global scale. We are seeking an experienced professional to own the ...

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All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Michigan

Data Science Product Manager information

See Michigan salary details

$44.9K

$138.9K

$171.7K

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

As of Sep 3, 2026, the average yearly pay for data science product manager in Michigan is $138,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,900.00 and $171,700.00 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 Michigan?

For Data Science Product Manager jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Science Product Manager jobs in Michigan look for?

The top searched job categories for Data Science Product Manager jobs in Michigan are:

What cities in Michigan are hiring for Data Science Product Manager jobs?

Cities in Michigan 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 Michigan as of August 2026, with employment types broken down into 80% Full Time, 19% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $138,936 per year, or $66.8 per hour.

Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Re-posted 12 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

13th of 45 rated automakers

Job description

The Commercial Analytics team is looking for a Data Scientist to join our team. Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar for model quality and reliability.
Data scientists work closely with data engineers, analysts, and business teams to design analytics solutions, implement advanced algorithms and evaluate the performance of use cases. Ideal candidates are self-motivated, inquisitive and creative, with a strong desire to solve real-world problems using data.
In this role, you will:
  • Collaborate with business stakeholders to identify high-impact opportunities for statistical and machine learning use cases
  • Design and implement econometric and causal inference models to quantify the impact of vehicle incentives, pricing, and commercial levers on sales, margin, and demand
  • Estimate and interpret price and incentive elasticities across brands, segments, and regions, informing pricing and go-to-market strategies
  • Develop defensible, well-documented methodologies that stand up to executive scrutiny and support strategic decision-making
  • Communicate complex results clearly to both technical and non-technical audiences
  • Partner with Data Engineers to define and source relevant data features for modeling as well as drive adoption and a deep understanding of proper data usage
  • Develop and validate predictive models using techniques such as regression, random forests, gradient boosting, causal modeling and neural networks
  • Communicate findings and recommendations to non-technical audiences through clear visualizations and storytelling
  • Contribute to the maintenance of models in production environments, ensuring scalability and performance
  • Conduct peer code reviews and support best practices in model development and deployment
  • Collaborate with both external and internal resources to support business requirements and key KPI measurement

Basic Qualifications:
  • Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics or other quantitative field)
  • Minimum of 5 years of experience in data science, econometrics or a related field
  • Proficiency in Python and SQL
  • Hands-on experience with big data and cloud platforms such as Databricks, Snowflake or Spark
  • Exposure to MLOps best practices, including model versioning, monitoring, and deployment pipelines
  • Strong grasp of machine learning algorithms like:
    • Regression (linear, logistic)
    • Causal Inference Models (Difference-in Difference, Regression Discontinuity Design)
  • Experience with experimental design, and statistical inference
  • Ability to translate complex data into actionable insights for business stakeholders

Preferred Qualifications:
  • Master's degree in a quantitative discipline (e.g., Statistics, Economics or other quantitative field)
  • Automotive experience
  • Tree-based models (Random Forest, XGBoost, LightGBM)
  • Clustering and dimensionality reduction (e.g., LDA, PCA, Dynamic Time Warping)
  • Experience using PySpark for distributed data processing and feature engineering
  • Experience with Power BI or similar tools for data visualization and dashboarding
  • 2+ years of experience working with finance / pricing / incentives data
  • 2+ years of experience working with sales / commercial data
  • Strong communication and storytelling skills with the ability to influence decision-makers
  • Understanding of CI/CD workflows for automating model testing and deployment
  • Experience working with real-time data pipelines and event-driven architectures

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