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Manager Data Scientist Jobs in Michigan (NOW HIRING)

Mentors the team of data scientists by guiding their professional development in conjunction with the team manager * Actively researches new technologies in related subjects and supports the ...

Mentors the team of data scientists by guiding their professional development in conjunction with the team manager * Actively researches new technologies in related subjects and supports the ...

Senior Data Scientist

Dearborn, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

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

Data Scientist - Conversational AI

Dearborn, MI · On-site

$120 - $180/hr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Act as a strategic partner to Product Managers. Challenge assumptions and define core ... Experience: 7+ years of experience in Data Science, Product Analytics, or Applied Machine Learning ...

As an AI/ML Data Scientist, you will be responsible for working with our customers to understand ... their manager}.This job may be eligible for relocation benefits. About GM Our vision is a world ...

As an AI/ML Data Scientist, you will be responsible for working with our customers to understand ... their manager}.This job may be eligible for relocation benefits. About GM Our vision is a world ...

Showing results 21-40

Manager Data Scientist information

See Michigan salary details

$40.1K

$143.8K

$212.2K

How much do manager data scientist jobs pay per year?

As of Aug 14, 2026, the average yearly pay for manager data scientist in Michigan is $143,829.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,400.00 and $148,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Manager Data Scientist, you need expertise in statistical analysis, machine learning, data modeling, and a relevant degree such as in computer science, mathematics, or statistics. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and experience with data visualization software and project management methodologies are commonly required. Strong leadership, effective communication, and the ability to mentor and guide teams are vital soft skills in this role. These competencies ensure successful project delivery, drive data-driven business decisions, and foster a productive, innovative team environment.

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

AspectManager Data ScientistData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; leadership experienceBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersAnalyzes data, develops models, reports findings
Employer & Industry UsageUsed in organizations with data teams, tech, finance, healthcareFound across industries, entry to mid-level roles

The main difference is that a Manager Data Scientist oversees data teams and projects, focusing on leadership and strategic planning, while a Data Scientist primarily conducts data analysis and model development. The manager role involves more coordination, mentorship, and stakeholder communication, whereas the data scientist role emphasizes technical skills and hands-on analysis.

How does a manager data scientist typically collaborate with cross-functional teams to drive business outcomes?

As a Manager Data Scientist, you will work closely with teams such as engineering, product management, and business stakeholders to ensure data-driven solutions align with company goals. This collaboration often involves translating complex analytical findings into actionable insights, setting project priorities, and managing expectations. You will also facilitate communication between data scientists and non-technical teams to foster understanding and ensure successful project delivery. Building strong relationships and promoting a culture of data-driven decision-making are essential aspects of the role.

What is a manager data scientist?

Manager Data Scientists are professionals who oversee data science teams and projects within an organization. They combine advanced analytical skills with leadership abilities to guide data scientists, set project priorities, and ensure data-driven strategies align with business goals. In addition to technical expertise in data modeling, machine learning, and analytics, they are responsible for mentoring team members, managing resources, and communicating insights to stakeholders. Their role bridges the gap between technical execution and strategic decision-making.

What are the most commonly searched types of Data Scientist jobs in Michigan?

The most popular types of Data Scientist jobs in Michigan are:

What cities in Michigan are hiring for Manager Data Scientist jobs?

Cities in Michigan with the most Manager Data Scientist job openings:

Infographic showing various Manager Data Scientist 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, with an average salary of $143,829 per year, or $69.1 per hour.

Expert Data Scientist

DTE Energy

Detroit, MI • On-site

Full-time

Re-posted 14 days ago


DTE Energy rating

8.6

Company rating: 8.6 out of 10

Based on 60 frontline employees who took The Breakroom Quiz

11th of 53 rated energy and utility


Job description

DTE is one of the nation's largest diversified energy companies. Our electric and gas companies have fueled our customer's homes and Michigan's progress for more than a century. And as Michigan's largest source of renewable energy, we're creating a cleaner, healthier environment to power our future. We're also serving communities beyond Michigan, where our affiliated businesses offer renewable energy, emission control technologies, and energy services to industries in 19 states.
But we're more than a leading energy company... and working at DTE is more than just a job. At DTE, we take great care of each other and our customers, and we use our energy to be a force for growth and prosperity in our communities. When you join us, you'll be part of a team that welcomes, recognizes, and celebrates differences and values everyone's health, safety, and wellbeing. Are you ready to make that kind of difference? Bring your energy to DTE. Together, we can achieve great things.
Testing Required: Not Applicable
Hybrid Role: This role is hybrid, with an established schedule of in-person work required at an assigned work location. Any remote work is expected to be performed from an employee's primary residence, unless allowed (or prohibited) through the Company's remote work guidelines.
Emergency Response: Yes - Must be available to perform a primary assignment in support of DTE's emergency response to storms or other events that impact service to our customers.
Job Summary
Acts as a technical expert and project leader for the most challenging data science projects. Provides highly technical and analytical assessments of business priorities to senior leadership and drives the implementation of analytic solutions. Acts as a strong influencer and change agent in the organization to advance a data-based decision-making culture. Oversees and coaches the team of data scientists to run analytical experiments methodically, evaluate alternative models, and develop predictive models to forecast business performance metrics. Communicates effectively with technical and non-technical stakeholders with strong domain expertise and business acumen. Leads the research and development of new technologies and best practices within the industry to recommend approaches and strategies that develop the organization's analytical capabilities-Span of Control: 0, Individual Contributor.
Key Accountabilities
  • Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating solutions into business processes
  • Conducts advanced statistical analysis to determine trends and significant data relationships, and proactively recommends areas of improvement
  • Develops complex data sets and predictive models to support key decisions to improve safety, employee engagement, operation efficiency, product quality, and customer satisfaction (e.g., cost-benefit, invest-divest, forecasting, predictive, what-if, impact analysis, etc.)
  • Prepares and delivers insightful presentations and action recommendations. Educates leaders and crews on complex analytical findings in laymen terms and with storytelling/data visualization
  • Identifies and evaluates technologies and provides strategic inputs to advance the organization's analytics capabilities
  • Mentors the team of data scientists by guiding their professional development in conjunction with the team manager
  • Actively researches new technologies in related subjects and supports the organization to develop data analytics strategies and roadmaps

Minimum Education & Experience Requirements
This is a multi-track base requirement job; education and experience requirements can be satisfied through one of the following options:
  • Bachelor's degree and 10 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
  • Master's degree and 8 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
  • Ph.D. degree and 6 years of experience, including 3 years of leading experience working as the team or project lead in a data analytical or computer programming function
  • 5 years of experience in qualitative and quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, predictive modeling, model optimization, time series analysis, cluster analysis, natural language processing/text analytics, and segmentation)

Other Qualifications
Preferred:
  • Master's or Ph.D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Econometrics, etc.)
  • Advanced business acumen and utility/energy industry experience
  • Deep interest and aptitude in data, metrics, analysis, trends, statistics, and program evaluation
  • Advanced project management skills
  • Experience with publications or conference presentations in a related subject

Other Requirements:
  • Intermediate-level competency using advanced Excel and statistical tools (e.g., Minitab, Alteryx, advanced Excel with VBA, R, Python, SAS, SPSS, Stata, MATLAB, etc.) to conduct in-depth analysis to support decision making
  • Proven expertise in articulating business questions and pulling data from relational databases (e.g., ORACLE, SQL SERVER)
  • Intermediate-to advanced-level programming skills in SQL, Python, R, and in visualization tools such as Power BI, Tableau
  • Intermediate- to advanced- level skills in data modeling, data structure, metadata, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Azure ADLS and Databricks)
  • Experience in designing, building, and supporting a production pipeline for data transformation and validation
  • Advanced skills of applied research design, machine learning, prediction, and optimization (e.g., multivariate statistical analysis, unsupervised and supervised learning, predictive modeling, Monte Carlo simulation)
  • Exceptional track record of successfully delivering large-scale analytical models and systems that result in substantial positive impact on business operations or customer satisfaction
  • Intermediate-level or higher Continuous Improvement knowledge, skills, and certifications
  • Self-starter and learning capability in advancing skillset in business processes, data science, and communications
  • Advanced interpersonal, analytical, and problem-solving skills, including the ability to communicate technical information and complex data analytics to a non-technical audience
  • Experience with leading large projects end-to-end with customer facing and system integration
  • Experience with mentoring and coaching data scientists
  • Experience with agile process development
  • Experience using version control (e.g., Git)

Additional Information
Incumbents may engage in all or some combination of the activities and accountabilities and utilize a variety of the competencies cited in this description depending upon the organization and role to which they are assigned. This description is intended to describe the general nature and level of work performed by incumbents in this job. It is not intended as an all-inclusive list of accountabilities or responsibilities, nor is it intended to limit the rights of supervisors or management representatives to assign, direct and control the work of employees under their supervision.
PRIVACY NOTICE TO CALIFORNIA JOB APPLICANTS
At DTE Energy, we are committed to providing an inclusive workplace where everyone feels welcome and a sense of belonging. We seek individuals with a heart for service, a passion to help our communities prosper, and ideas to help shape the future of energy. We are proud to be an equal opportunity, employer that considers all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, age, religion, disability, national origin, citizenship, height, weight, genetic information, marital status, pregnancy, protected veteran status or any other status protected by applicable federal and/or state laws.

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