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Data Scientist Project Manager Jobs in Michigan (NOW HIRING)

Data Scientist Role Summary OneMagnify's Data Scientists sit at the intersection of client strategy ... Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and ...

Data Scientist Role Summary OneMagnify's Data Scientists sit at the intersection of client strategy ... Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and ...

Conduct analyses to address ad hoc requests of ongoing project work. Assist in developing the ... Ability to work under general supervision while managing multiple routine tasks. * Familiarity with ...

Conduct analyses to address ad hoc requests of ongoing project work. Assist in developing the ... Ability to work under general supervision while managing multiple routine tasks. * Familiarity with ...

Conduct analyses to address ad hoc requests of ongoing project work. Assist in developing the ... Ability to work under general supervision while managing multiple routine tasks. * Familiarity with ...

The Senior Data Scientist will design and implement advanced systems that support cross-domain ... management leases Tuition assistance Established and active employee resource groups Paid time off ...

Data Scientist

Dearborn, MI ยท On-site +1

$107K - $182K/yr

... SQL for querying, managing, and optimizing relational databases. 3. Applying mathematical ... Data Scientist - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a ...

Drive projects independently while effectively managing stakeholder expectations and timelines ... Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics ...

Lead Data Scientist, Healthcare Analytics works with system leaders, business stake holders and ... The position requires a team lead mindset who is ready to lead and deliver the projects using agile ...

Infrastructure Management: Building and maintaining the infrastructure for AI development, data pipelines, and automated workflows. * Collaboration: Working with data scientists to define AI ...

Lead Data Scientist, Healthcare Analytics works with system leaders, business stake holders and ... The position requires a team lead mindset who is ready to lead and deliver the projects using agile ...

Industry/Sector Not Applicable Specialism Data Science Management Level Director & Summary The ... multiple projects while maintaining executive-level client relations. You will inspire others by ...

Showing results 21-40

Data Scientist Project Manager information

What are the key skills and qualifications needed to thrive as a data scientist project manager?

To thrive as a Data Scientist Project Manager, you need a solid background in data science, analytics, and project management, often supported by degrees in computer science, statistics, or business and certifications like PMP or Agile. Familiarity with tools such as Python, R, SQL, project management software (e.g., Jira, Trello), and cloud platforms is crucial. Excellent communication, leadership, and problem-solving abilities help bridge gaps between technical teams and stakeholders. These skills ensure successful project delivery by aligning data-driven insights with business objectives and effective team coordination.

What is a data scientist project manager?

A Data Scientist Project Manager is a professional who oversees data science projects from conception through completion, ensuring that project goals align with business objectives. They bridge the gap between data science teams and stakeholders, managing timelines, resources, and communication. In addition to technical knowledge in data science and analytics, they possess strong project management skills to coordinate tasks, mitigate risks, and deliver results. Their role is essential for translating complex data-driven insights into actionable business strategies. They often use methodologies like Agile or Scrum to guide project workflows and adapt to changing requirements.

Can a data scientist become a data scientist project manager?

A data scientist can become a data scientist project manager by developing leadership, communication, and project management skills, often through experience and certifications like PMP or Agile. Transitioning typically involves gaining experience in managing projects and teams while maintaining technical expertise in data analysis and modeling.

What is the difference between Data Scientist Project Manager vs Data Analyst Project Manager?

AspectData Scientist Project ManagerData Analyst Project Manager
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related fields; certifications like PMP or AgileBachelor's in Data Analysis, Business, or related fields; certifications like PMP or Agile
Work EnvironmentLeads data science projects, collaborates with data scientists and engineersManages data analysis projects, works with analysts and business teams
Employer & Industry UsageTech companies, finance, healthcare, industries with advanced analyticsRetail, marketing, finance, industries relying on data reporting

The main difference is that Data Scientist Project Managers oversee data science initiatives involving complex modeling and algorithms, while Data Analyst Project Managers focus on managing data reporting and analysis projects. Both roles require project management skills and relevant certifications, but their technical focus and team collaboration differ.

How do data scientist project managers typically balance technical data work with project management responsibilities?

Data Scientist Project Managers often split their time between hands-on data analysis and overseeing project progress. They commonly coordinate with cross-functional teams, set project timelines, and ensure that data solutions align with business objectives while occasionally contributing code or analytical insights. Effective communication and time management are essential, as they must bridge the gap between technical teams and stakeholders. This dual responsibility offers exposure to both technical growth and leadership development, making it ideal for professionals seeking advancement into higher management roles.
What are popular job titles related to Data Scientist Project Manager jobs in Michigan? For Data Scientist Project Manager jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Data Scientist Project Manager jobs? Cities in Michigan with the most Data Scientist Project Manager job openings:
Infographic showing various Data Scientist Project Manager job openings in Michigan as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Data Scientist

Conclusive Marketing

Detroit, MI โ€ข On-site

Full-time

Posted 19 days ago


Job description

Data ScientistRole Summary

OneMagnify's Data Scientists sit at the intersection of client strategy and technical delivery, turning complex business questions into models, analyses, and insights that clients actually use to make decisions. You'll work alongside Data Engineering, AI, and cross-functional teams to design and deploy solutions that span the full analytics lifecycle, from data integration and quality to predictive modeling and advanced analytics. This role is a fit for someone who wants to do serious technical work and see it matter in the real world.

The Impact You'll Have

The clients you'll support are making high-stakes decisions about customers, markets, and products. Your models, including forecasting demand, segmenting audiences, and optimizing spend, become the analytical backbone of how they operate. When your work is right, it drives measurable outcomes. When it's wrong, someone notices. That accountability is part of what makes this role interesting.

You'll also contribute to building the analytics capabilities OneMagnify delivers at scale. That means writing code and documentation that others can reproduce, maintain, and extend. Shipping a model is the beginning, not the end. Cross-functional collaboration with engineering, strategy, and delivery teams is part of the daily rhythm, and your ability to translate between technical and business contexts will be used constantly.

The work spans industries and problem types (automotive, retail, financial services, and more) so you'll develop breadth alongside depth. You'll rarely work on the same type of problem twice in a row.

What You'll Do

Build and validate analytical models

  • Design, deploy, and monitor models including forecasting, classification, regression, and segmentation
  • Conduct A/B testing and causal analyses with rigorous experimental design and clear documentation
  • Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure reproducibility across the full model lifecycle

Own data integration and quality

  • Integrate data from multiple sources and develop data-quality reporting that surfaces issues before they become client problems
  • Conduct root-cause analysis on data anomalies and validate database changes prior to release
  • Use Databricks for large-scale data processing and machine learning workflows

Translate requirements into technical solutions

  • Partner with business and engineering teams to elicit requirements, define business rules, and turn them into technical specifications
  • Document solutions clearly enough that someone else can maintain and extend your work
  • Ensure alignment between what clients ask for and what gets built

Communicate findings to varied audiences

  • Synthesize and present analytical findings to internal and external stakeholders, including executive-level audiences, with the judgment to handle complex or sensitive inquiries with care
  • Build metrics and KPI reports that inform real business decisions, not just dashboards that get ignored
  • Prepare visualizations in Tableau and Power BI that make complex outputs accessible

Support collaborative development

  • Use Git/GitLab for version control, reproducibility, and collaborative code development
  • Collaborate with engineering teams to implement MLOps practices including model deployment, monitoring, and end-to-end lifecycle management using tools such as MLflow
  • Adhere to data governance, privacy, and compliance standards across all work
What You'll Need
  • BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related quantitative field - or equivalent practical experience
  • 2-5+ years of hands-on analytics including predictive modeling, A/B testing, and optimization
  • Advanced SQL and Python; strong ability to query, manipulate, and interpret data from databases and data warehouses
  • Hands-on experience with Databricks for large-scale data processing and machine learning workflows
  • Proficiency with Tableau and/or Power BI for visualization and reporting
  • Experience with Git/GitLab for version control and collaborative development
  • Strong Excel and PowerPoint skills
  • Proven ability to present analyses to management and collaborate with both business and technical stakeholders
  • Experience diagnosing and resolving data-quality issues across multiple platforms
  • Understanding of data governance, privacy, and compliance standards
  • Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and integration
Future-Ready Skills (Nice to Have)
  • Proficiency with SAS or R in an applied analytics environment
  • Familiarity with automotive or VIN data and complex industry-specific data structures
  • Exposure to AI-enabled analytics workflows or automation within a data science context
  • Experience working in integrated marketing, consulting, or digital services environments where analytics supports client-facing delivery