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Applied Statistician Jobs in Michigan (NOW HIRING)

Who is proficient in Applied Statistics/Econometrics, Statistical Programming, Database Marketing Management & Operations etc. Who is proficient in Customer-level data analysis. Qualifications Who ...

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Minimum 5 years of experience in data science, machine learning, or applied statistics * Strong experience with Databricks (critical requirement) * Proficiency in Python (Pandas, NumPy, scikit-learn ...

Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative ...

Lead AI and Data Science Engineer II

Midland, MI · On-site

$88K - $115K/yr

Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative ...

Machine Learning Engineer

Auburn Hills, MI

$108K - $130K/yr

Minimum 5 years of experience in data science, machine learning, or applied statistics * Strong experience with Databricks (critical requirement) * Proficiency in Python (Pandas, NumPy, scikit-learn ...

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Applied Statistician information

See Michigan salary details

$35.3K

$72.9K

$102K

How much do applied statistician jobs pay per year?

As of Aug 12, 2026, the average yearly pay for applied statistician in Michigan is $72,915.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,700.00 and $101,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an applied statistician, and why are they important?

To thrive as an Applied Statistician, you need strong quantitative skills, a solid background in statistics or mathematics, and typically at least a bachelor's or master's degree in a related field. Familiarity with statistical software such as R, SAS, Python, or SPSS, and experience with data management systems are commonly required. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and conveying findings to stakeholders. These skills ensure accurate data analysis, effective decision-making, and clear presentation of complex statistical concepts in real-world applications.

What is the difference between Applied Statistician vs Data Analyst?

AspectApplied StatisticianData Analyst
Required CredentialsDegree in Statistics, Mathematics, or related field; often certifications in statistical softwareDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentResearch settings, industries like healthcare, finance, manufacturing; focus on statistical modelingBusiness environments, marketing, finance; focus on data interpretation and reporting
Employer & Industry UsageEmployers seeking advanced statistical analysis for decision-makingOrganizations needing data-driven insights for operational improvements

Applied Statisticians and Data Analysts both work with data, but Applied Statisticians focus more on developing statistical models and methods, often requiring advanced statistical knowledge. Data Analysts typically handle data cleaning, visualization, and reporting to support business decisions. While their skills overlap, their roles differ in complexity and focus, with Applied Statisticians often involved in more technical, research-oriented tasks.

What are some common challenges an applied statistician faces when working with cross-functional teams?

Applied Statisticians often work closely with professionals from diverse backgrounds, such as engineers, business analysts, and subject matter experts. One common challenge is translating complex statistical concepts into actionable insights for non-technical stakeholders. Additionally, balancing the need for methodological rigor with practical constraints like tight deadlines and limited data quality can be demanding. Success in this role often depends on strong communication skills, adaptability, and the ability to collaborate effectively to ensure statistical analyses drive meaningful decisions.

What is a good salary for an applied statistician?

The average salary for an applied statistician varies by experience, location, and industry but typically ranges from $70,000 to $120,000 annually. Senior roles or those with specialized skills in data analysis, programming, and statistical software can earn higher salaries, often exceeding $130,000.

What is an applied statistician?

An applied statistician is a professional who uses statistical methods and techniques to collect, analyze, and interpret data in order to solve real-world problems. They work across various industries, such as healthcare, finance, government, and technology, to inform decision-making and improve processes. Applied statisticians design experiments, develop predictive models, and communicate their findings to stakeholders, often using specialized software and programming languages. Their work supports evidence-based strategies and helps organizations make informed choices.

What jobs use applied statistics?

Applied statisticians work in various fields such as healthcare, finance, marketing, government, and technology, applying statistical methods to analyze data and inform decision-making. They often use tools like R, SAS, or Python and may work in research, data analysis, or consulting roles. These jobs typically require strong analytical skills and knowledge of statistical techniques and software.

What does an applied statistician do?

As an applied statistician, you apply statistical formulas and analysis to real-world situations. Your responsibilities and the scope of your job vary depending on the needs of your employer. You may develop a plan to collect data, perform analysis using statistical methods, and formulate a report on your findings. You may also use statistical analysis to solve specific problems or identify trends in an organization, a city, or an industry. You also use computer software to organize and analyze large amounts of data.

What are popular job titles related to Applied Statistician jobs in Michigan? For Applied Statistician jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Applied Statistician jobs in Michigan look for? The top searched job categories for Applied Statistician jobs in Michigan are:
What are popular job titles related to Applied Statistician jobs in MI? For Applied Statistician jobs in MI, the most frequently searched job titles are:
Infographic showing various Applied Statistician job openings in Michigan as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $72,915 per year, or $35.1 per hour.

Data Scientist Statistician Lead - Product Safety Data Analytics

General Motors

Warren, MI • On-site

$120 - $180/hr

Other

Re-posted yesterday


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 306 frontline employees who took The Breakroom Quiz

7.4

Company rating compared to similar companies: 7.4 out of 10

Automakers average

Based on 6,274 frontline employees who took The Breakroom Quiz


Job description

The Role

The Product Safety Data Analytics team is seeking highly motivated and qualified candidates for the position of Data Scientist Statistician Lead.

This is a great opportunity for an innovative data scientist/statistician and technical leader with extensive hands‑on experience across the full end‑to‑end data science lifecycle. This technical leader role requires extensive programming skills and deep knowledge of statistical techniques to solve complex problems and provide guidance to a team of data scientists focused on advanced statistical analysis, predictive modeling, and data‑driven decision support. You will be part of a highly collaborative team that values growth, creativity, and a relentless focus on business impact through analytics.

In this role, you will be responsible for leading the development of scalable solutions to identify and analyze potential emerging vehicle safety issues. You will work with business partners to understand their challenges and needs, develop appropriate statistical analyses, lead proof‑of‑concept efforts for new analytical capabilities, and provide technical expertise and guidance to a team of data scientists.

At General Motors, our product teams are redefining mobility. Through a human‑centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard— from breakthrough hardware and battery systems to intuitive design, intelligent software, and next‑generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

What You’ll Do (Responsibilities)
  • Develop and standardize best practices for continuously monitoring emerging safety issues for use in safety hazard monitoring
  • Raise the bar on safety‑investigation data‑analytics support by continuously integrating effective analytical solutions and developing a feedback loop for tool and process improvements
  • Correctly perform appropriate statistical data analyses to provide unbiased results
  • Continuously drive efficiencies by implementing automation opportunities using a combination of custom software development and integration of off‑the‑shelf solutions
  • Develop and refine statistical and machine learning models to solve complex business problems
  • Prototype new analytical approaches and decision‑support solutions to address business needs
  • Develop workflow automation and scalable analytical tools to streamline business processes
  • Identify long‑term technical innovations while continuously improving execution efficiency
  • Exhibit the ability to tell a succinct, data‑driven story in any forum and tailor delivery to a wide range of stakeholder levels, from analyst to senior executive
  • Apply strong business acumen, highly specialized knowledge, and organizational expertise to establish and advance new data‑analytics support areas
Your Skills & Abilities (Required Qualifications)
  • 8+ years of work experience in applied statistics, machine learning, engineering, or data science, or 6+ years of work experience with Ph.D.
  • M.S. in a quantitative discipline (Statistics, Mathematics, Econometrics, Operations Research, or other relevant degree)
  • Strong background in varied statistical data analyses such as reliability analysis, analysis of variance, time series, categorical data analysis, multivariate analysis, and sampling design
  • Strong background in anomaly detection, diagnostics and prognostics, and root cause analysis
  • Demonstrated experience in large‑scale data analytics
  • Programming & Frameworks: Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit‑learn, SQL
  • Machine Learning & Advanced Analytics: supervised and unsupervised learning, natural language processing, decision trees, clustering, anomaly detection, and predictive modeling
  • Data Engineering: Databricks, SQL, data pipelines, data preprocessing, and feature engineering
  • Ability to effectively communicate results and methodologies; must be comfortable presenting to executive leadership
  • Strong work ethic, drive for results, and the ability to work in an ambiguous workspace
  • Understanding of vehicle safety technologies including design intent, function, and intended performance in the field
What Will Give You a Competitive Edge (Preferred Qualifications)
  • Ph.D. in a quantitative discipline (Statistics, Mathematics, Econometrics, Operations Research, or other relevant degree)
  • 10+ years of work experience in applied statistics, machine learning, engineering, data science, or a related field
  • Deep knowledge of GM’s Data Ecosystem
  • Deep knowledge of GM’s Cloud Technology Stack for Data Science
  • SME in applied reliability/survival analysis
  • Experience in vehicle development or validation of safety‑related systems or components
  • Experience taking advanced analytics solutions from business problem statement through deployment and ongoing optimization
  • Experience developing and deploying production‑grade statistical or machine learning solutions that have delivered significant business value

Company vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, though which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908