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Data Science 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 ...

Cavallo Solutions

Data Scientist

Grand Rapids, MI · On-site

Using our customers' data and advanced data science, we are building products that allow our customers to flourish and thrive. Data is a pillar of our core values; it fuels more informed and ...

OpTech

Data Science Analyst (VB/SQL)

Detroit, MI · Remote

Data Science Analyst Why work at OpTech? OpTech is a woman-owned company that values your ideas, encourages your growth, and always has your back. When you work at OpTech, not only do you get health ...

Cavallo Solutions

Data Scientist

Grand Rapids, MI · On-site

Using our customers' data and advanced data science, we are building products that allow our customers to flourish and thrive. Data is a pillar of our core values; it fuels more informed and ...

Deloitte

AI and Data Science Engineer III

Detroit, MI

$113K - $136K/yr

AI Data Science Engineer III Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring a Senior ...

Denso

Data Scientist 2

Southfield, MI · On-site

$90K - $113K/yr

Contribute to and help establish analytics and data science standards, methodologies, and best practices for process improvement initiatives. * Support training and enablement of associates on new ...

Tech Tammina LLC

Data Scientists Modeling

Dearborn, MI · On-site

... data science problems and analytical tasks. • Develop, train, and evaluate statistical and machine learning models to address specific business needs (e.g., prediction, classification, clustering ...

Denso

Data Scientist 2

Southfield, MI

$90K - $113K/yr

Contribute to and help establish analytics and data science standards, methodologies, and best practices for process improvement initiatives. * Support training and enablement of associates on new ...

Deloitte

AI and Data Science Engineer III

Detroit, MI · On-site +1

$113K - $136K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

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All JobsData Science JobsData Science Jobs in Michigan

Data Science information

See Michigan salary details

$32.7K

$107K

$171.3K

How much do data science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for data science in Michigan is $106,978.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $118,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Michigan? The most popular types of Data Science jobs in Michigan are:
What are popular job titles related to Data Science jobs in Michigan? For Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Michigan look for? The top searched job categories for Data Science jobs in Michigan are:
What cities in Michigan are hiring for Data Science jobs? Cities in Michigan with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Michigan as of May 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $106,978 per year, or $51.4 per hour.
Data Scientist

Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 16 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 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

What Stellantis employees say

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