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Applied Data Science Jobs in Michigan (NOW HIRING)

Little Caesars

VP, Global Data & Analytics

Detroit, MI · On-site

Bachelor's degree in Computer Science, Engineering, Statistics, Applied Mathematics or a related field. * Minimum of fifteen (15) years working in data pipelines, data warehouse, data analytics, data ...

GripFusion

Internship Opportunities

Ann Arbor, MI · On-site

We operate at the intersection of hardware, software, data science, and applied biomechanics, turning high-resolution grip and motion data into actionable performance insights. We are well-funded for ...

GripFusion

Internship Opportunities

Ann Arbor, MI · On-site

We operate at the intersection of hardware, software, data science, and applied biomechanics, turning high-resolution grip and motion data into actionable performance insights. We are well-funded for ...

THOMSON REUTERS

Lead Applied Scientist

Ann Arbor, MI · Hybrid

You will develop a deep understanding of customer problems and the data that informs them. About You You're a fit for the role of Lead Applied Scientist if your background includes: * PhD or Master ...

Ford Motor Company

AI Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT) 3+ years of experience of analytical methods and their proper application 3+ years of experience using AI ...

Ford Motor Company

AI Engineer

Dearborn, MI · On-site +1

$105K - $126K/yr

Bachelor's Degree in Data Science, Predictive Analytics, Statistics, Applied Mathematics, Physics, AI, Computer Science, or a related quantitative field * Master's Degree in a related field is ...

THOMSON REUTERS

Senior Research Engineer

Ann Arbor, MI · Hybrid

$102K - $140K/yr

Experience collaborating with applied data scientists to translate research work in production ready solutions * A keen interest in real-world applications and impact. * Experience with cloud ...

Stellantis

Quality Technical Manager

Auburn Hills, MI · On-site

You will lead a talented team of data analysts/scientists, driving predictive analytics and early ... Solid understanding of statistics, exploratory data analysis, and applied machine learning

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Applied Data Science information

What are the typical responsibilities of an Applied Data Science professional on a day-to-day basis?

An Applied Data Science professional typically spends their days gathering, cleaning, and analyzing structured and unstructured data to uncover patterns and generate actionable insights. They frequently build and deploy predictive models, collaborate with business and engineering teams to define project requirements, and communicate findings through clear reports or visualizations. Additionally, they often engage in regular team meetings, contribute to ongoing process improvements, and continuously learn new technologies or methodologies to enhance project outcomes. This combination of technical and collaborative work makes the role both dynamic and highly impactful within most organizations.

What are the key skills and qualifications needed to thrive in the Applied Data Science position, and why are they important?

To thrive in Applied Data Science, you need a strong background in statistics, machine learning, data analysis, and programming languages such as Python or R, typically evidenced by a degree in a quantitative field. Familiarity with data visualization tools (like Tableau), cloud platforms (AWS, GCP), and certifications in data science or analytics are highly valued. Effective communication, problem-solving, and teamwork are crucial soft skills to convey insights and collaborate with both technical and non-technical stakeholders. These competencies are critical for transforming complex data into actionable business strategies and driving measurable impact within organizations.

What is an Applied Data Science job?

An Applied Data Science job focuses on using data science techniques to solve real-world problems in business, healthcare, finance, and other industries. It involves collecting, processing, analyzing, and interpreting large datasets to extract meaningful insights. Applied data scientists use machine learning, statistical modeling, and programming skills to develop data-driven solutions. They work closely with stakeholders to implement models that drive decision-making and improve operations.

What are popular job titles related to Applied Data Science jobs in Michigan? For Applied Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Applied Data Science jobs in Michigan look for? The top searched job categories for Applied Data Science jobs in Michigan are:
What cities in Michigan are hiring for Applied Data Science jobs? Cities in Michigan with the most Applied Data Science job openings:
Applied Data Science jobs near you
Infographic showing various Applied Data Science job openings in Michigan as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Detroit, MI • On-site, Remote

$152K - $158K/yr

Full-time

Posted 6 days ago

Job description

Senior Product Manager, Life Sciences Data Products (Applied AI)

Location: U.S. (Remote-first) with optional hub-based hybrid
Employment: Full-time
Level: Senior IC (high ownership)
Start: ASAP / Flexible

Beacon Talent is leading a confidential search for a venture-backed company building an applied AI + data platform that supports life sciences teams (biopharma, medtech, and research organizations) with secure access to real-world clinical datasets and tooling that accelerates discovery and development while maintaining high standards for privacy, quality, and responsible use.

The Role

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

This is a hands-on, high-agency role—ideal for a PM who loves ambiguous problem spaces, can translate market signals into crisp product bets, and can partner deeply with engineering and data teams to ship scalable product capabilities.

What You’ll Own

  • Product vision & roadmap: Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.

  • Discovery & validation: Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.

  • Scalable data products: Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.

  • AI-assisted workflows: Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).

  • Execution leadership: Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.

  • Cross-functional alignment: Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.

  • Market awareness: Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

What We’re Looking For

Required

  • 5+ years building data products or platforms for life sciences and/or healthcare customers.

  • Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.

  • Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).

  • Track record partnering with engineering and data teams to deliver complex, high-impact product work.

  • Excellent communication—credible with technical teams and clear with non-technical stakeholders.

  • Comfort operating in a fast-moving environment with evolving inputs and limited process.

Nice to have

  • 0→1 product experience or taking early products to scale in a regulated domain.

  • UX/product design sensibility with strong intuition for end-user workflows.

  • Prior experience in analytics, data science, or experimentation.

  • Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Why This Role

  • Direct ownership of a high-impact roadmap at the intersection of life sciences + data platforms + applied AI

  • Meaningful influence over what becomes productized vs. service-heavy

  • Close collaboration with technical leadership and high visibility across the company

Compensation

Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)