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# Statistical Scientist Ph.D.

- **Company:** Exponent
- **Location:** Farmington Hills, MI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, C++ (Programming Language), Computer Programming, R (Programming Language), Python (Programming Language), SAS (Software), SQL Databases, Visual Basic Language
- **Published:** July 16, 2026
- **Apply:** https://jobs.mitalent.org/job-seeker/job-details/JobCode/395202408

## About the Role

Ph.D. in Statistics or Applied Mathematics
Significant research in theoretical or applied statistical methods
Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences
Experience or capabilities in such subject areas as statistical data mining, analysis of reliability and life data, sampling plan development, experimental design, or quality control/improvement
Minimum of 2 years' experience with one or more statistical software packages (e.g., R, SAS, Python)
Ability to work independently and in multidisciplinary teams
Programming skills (e.g., R, C++, SQL, Visual Basic, Python), software or dashboard development experience are strongly preferred
Applicants are encouraged to submit a CV with publications (feel free to include publications that are in review or pending) [not restricted to 1 page].

## Description

We are currently seeking a Statistical Scientist for our Data Sciences Practice in Farmington Hills, MI. In this role, you will work as part of a team to help our clients solve challenging technical problems which are often urgent, high profile, and multi-disciplinary. You will be involved in a variety of projects in application areas including manufacturing, construction, automobiles, health, and consumer products. You will have the opportunity to define and shape your individual consulting practice based on your skills and interests.

You will be responsible for

Participating in diverse projects involving exploratory data analysis, statistical inference, and predictive modeling
Applying risk analysis methodologies to problems in engineering, manufacturing, health, finance, and the environment
Providing support to internal and external clients when planning data collection, including framing the problem, experimental design, sample size calculations, and identifying appropriate populations and sampling strategies
Developing reports and visualizations to address clients' scientific and engineering problems and to support litigation


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