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Data Scientist Jobs in Rochester Hills, MI (NOW HIRING)

Stellantis

Data Scientist

Auburn Hills, MI · On-site

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 ...

Geologics

Data Scientist

Sterling Heights, MI · Hybrid

$52 - $62/hr

  • PTO

Role: Data Scientist Client: Top Aerospace and Defense company Location: Sterling Heights, MI - Hybrid (Goal is to be 3 days on, 2 day remote) Schedule/Travel: 9/80 with 10% travel Education:

Stellantis

Data Scientist

Auburn Hills, MI

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

Geologics

Data Scientist

Sterling Heights, MI · Hybrid

$52 - $62/hr

  • PTO

Role: Data Scientist Client: Top Aerospace and Defense company Location: Sterling Heights, MI - Hybrid (Goal is to be 3 days on, 2 day remote) Schedule/Travel: 9/80 with 10% travel Education:

Ford Motor Company

Data Scientist

Dearborn, MI · On-site

$85K - $192K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

As a Data Scientist at Ford, you will serve as a domain expert in at least one core data science discipline (e.g., NLP, Generative AI, Computer Vision, forecasting, or prognostics), applying deep ...

OneMagnify

Data Scientist

Detroit, MI · On-site

$120 - $170/hr

Data Scientist Role 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 ...

Conclusive Marketing

Data Scientist

Detroit, MI

Data Scientist Role 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 ...

OneMagnify

Data Scientist

Detroit, MI · On-site

Data Scientist Role 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 ...

Rocket Limited Partnership

Data Scientist

Detroit, MI · On-site

As the Data Scientist, you'll be responsible for performing exploratory data analysis, feature engineering and predictive modeling to provide actionable insights and strategic direction for business ...

Rock Connections

Data Scientist

Detroit, MI

As the Data Scientist, you'll be responsible for performing exploratory data analysis, feature engineering and predictive modeling to provide actionable insights and strategic direction for business ...

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

The Senior Data Scientist will design and implement advanced systems that support cross-domain manufacturing analytics. This role operates at the intersection of optimization, enterprise data ...

Ford Motor Company

Data Scientist

Dearborn, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Master's degree in Statistics, Data Science, Econometrics, Engineering, Physics, or related quantitative field or a combination of education and equivalent work experience * 3+ years of hands-on ...

Ford Motor Company

Data Scientist

Dearborn, MI · On-site +1

$107K - $182K/yr

  • Medical

  • Dental

  • Life

  • PTO

Data Scientist - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the anticipated worksite. Hence ...

DTE Energy

Expert Data Scientist

Detroit, MI · On-site

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating ...

DTE Energy

Expert Data Scientist

Detroit, MI

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating ...

Td

Principal Data Scientist (US)

Southfield, MI

$148K - $223K/yr

In addition, the Principal Data Scientist provides technical expertise with a focus on bank and industry-wide solutions that addresses capability gaps to create opportunities for significant value ...

TD Bank Group

Principal Data Scientist (US)

Southfield, MI · On-site +1

$148K - $223K/yr

In addition, the Principal Data Scientist provides technical expertise with a focus on bank and industry-wide solutions that addresses capability gaps to create opportunities for significant value ...

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All JobsData Scientist JobsData Scientist Jobs in Rochester Hills, MI

Data Scientist information

See Rochester Hills, MI salary details

$34.5K

$113K

$180.9K

How much do data scientist jobs pay per year?

As of Aug 15, 2026, the average yearly pay for data scientist in Rochester Hills, MI is $112,975.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,700.00 and $125,200.00 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, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What do data scientists do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and employment opportunities continue to grow as organizations seek to leverage big data for competitive advantage.

Is data science a math heavy field?

Data scientists rely heavily on mathematics, including statistics, linear algebra, and calculus, to analyze data and develop models. Strong math skills are essential for tasks like machine learning, data analysis, and algorithm development, often complemented by programming in languages such as Python or R. However, practical skills in data manipulation and domain knowledge are also important for success in the field.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What are some typical projects data scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.
More about Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in Rochester Hills, MI?

The most popular types of Data Scientist jobs in Rochester Hills, MI are:

What are popular job titles related to Data Scientist jobs in Rochester Hills, MI?

For Data Scientist jobs in Rochester Hills, MI, the most frequently searched job titles are:

What job categories do people searching Data Scientist jobs in Rochester Hills, MI look for?

The top searched job categories for Data Scientist jobs in Rochester Hills, MI are:

What cities near Rochester Hills, MI are hiring for Data Scientist jobs?

Cities near Rochester Hills, MI with the most Data Scientist job openings:

Data Scientist jobs near you
Infographic showing various Data Scientist job openings in Rochester Hills, MI as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $112,975 per year, or $54.3 per hour.

Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Re-posted 23 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th 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

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