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Data Science Insurance Jobs in Michigan (NOW HIRING)

... science/predictive analytics experience in (re)insurance or 4 or more years predictive modeling experience in another industry. * Sr. Data Scientist: 4 or more years of data science/predictive ...

Data architect

Lansing, MI · On-site

$64.75 - $83.25/hr

... Science, Insurance, legal, healthcare, among others. It also offers outsourcing, consulting ... Job Title: Data Architect Duration: 12+ Months Location: Lansing, MI Complete Description ...

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

Mentor and provide guidance to junior data scientists and analysts, fostering a culture of ... Life insurance and accidental death & dismemberment insurance Compensation Range Compensation may ...

Data Architect Specialist

Dearborn, MI

$58.50 - $75.25/hr

Collaborate with data engineers, architects, analysts, and data scientists to design and deliver ... Life Insurance (100% paid) * 401(k) with immediate vesting and 3% (of salary) dollar-for-dollar ...

Sr. Data Analyst

Ypsilanti, MI

$77K - $98K/yr

Bachelor's degree in computer science, data science, statistics, or an engineering-related ... Life Insurance * Generous Paid Time Off, Including Vacation, Sick, and Abundant Holidays

Build and lead high-performing teams of data scientists, analytics engineers, and AI product ... Various Optional Insurance programs such as legal, identity theft, critical illness, etc. * Tuition ...

The ideal candidate will partner with business, engineering, analytics, and data science teams to ... insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.

Auto-Owners Insurance, a top-rated insurance carrier, is seeking a motivated Data Specialist to ... Bachelor's degree in mathematics, statistics, actuarial science, data science, or related field is ...

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Showing results 1-20

Data Science Insurance information

See Michigan salary details

$20.2K

$95.2K

$179.6K

How much do data science insurance jobs pay per year?

As of Jul 9, 2026, the average yearly pay for data science insurance in Michigan is $95,199.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,665.00 and $135,238.00 per year, depending on experience, location, and employer.

What is a Data Science Insurance job?

A Data Science Insurance job involves using data analytics, machine learning, and statistical modeling to assess risks, detect fraud, optimize pricing, and enhance customer experience in the insurance industry. Professionals in this role analyze large datasets to identify patterns and trends that help insurers make data-driven decisions. They work with actuarial teams, underwriters, and claims departments to improve risk assessment and operational efficiency. This role requires expertise in programming languages like Python or R, as well as proficiency in data visualization, predictive modeling, and big data processing.

What are some common challenges faced by data scientists working in the insurance industry?

Data scientists in the insurance sector often encounter challenges like working with large, complex, and sometimes incomplete datasets, as well as navigating strict regulatory frameworks. Balancing the need for highly accurate predictive models with the business's risk appetite and operational constraints is a key aspect of the job. Additionally, there's a strong emphasis on explaining complex analytical findings to non-technical stakeholders such as underwriters, actuaries, or business managers. These challenges foster collaborative problem-solving and help data science professionals sharpen both their technical and communication skills in a real-world environment.

What are the key skills and qualifications needed to thrive in the Data Science Insurance position, and why are they important?

To thrive in Data Science Insurance, you need strong analytical skills, proficiency in statistical modeling, and a solid foundation in mathematics and insurance principles, often supported by a degree in data science or actuarial science. Experience with programming languages like Python or R, data visualization tools, and knowledge of insurance-specific software or relevant certifications like ACAS or CSPA are highly valued. Excellent problem-solving abilities, attention to detail, and clear communication skills are essential for translating complex data into actionable insights for diverse teams. These competencies enable professionals to accurately assess risk, improve decision-making, and drive innovation within insurance organizations.

What are the most commonly searched types of Data Science Insurance jobs in Michigan? The most popular types of Data Science Insurance jobs in Michigan are:
Data Scientist - Modeling and Analytics

Data Scientist - Modeling and Analytics

AAA Life Insurance Company

Livonia, MI

Full-time

Re-posted 21 days ago


Job description

Why AAA Life

AAA Life is a respected and trusted American brand that has been focusing on Life Insurance and Annuity Products since 1969. At AAA Life we have over 1.8 million policies where we take pride in earning the trust of our policyholders who understand our promise to be there for them – and their families – when we’re needed most. By joining the AAA Life team, you are joining a company that genuinely cares about helping each other, with a devotion to protect the lives of those around us. We embrace a diverse, equitable, inclusive culture where all associates can feel a sense of belonging and use their unique talents and perspective to influence, innovate, motivate, and thrive.

How You’ll Work

Work Solution: Hybrid 


What You'll Do

As a Data Scientist – Modeling and Analytics, you will be responsible for creating statistical models and performing analyses that drive sales and policy growth for the organization. You will partner with marketing team members, marketing managers, and other data analysts and scientists to identify business needs, gather data, build, and maintain effective models, and assess model performance over time. This role requires proficiency in SQL for data manipulation, Sagemaker or other AI/ML tools for model building, R or Python for data analysis, and a visualization tool such as PowerBI for quickly assessing model performance. 
  • Build, maintain, and automate models to predict purchase propensity, policy premium, policy lapse/retention, cross-selling, upselling, next best action, and other consumer behaviors using both internal data, census data, appended aggregated data, and macroeconomic data. Recommend marketing distribution strategies leveraging data and models.  
  • Conduct advanced exploratory data analysis. Perform model interpretability and explainability analysis.  
  • Leverage specific metrics for model performance evaluation (e.g., precision, recall, F1 score). Implement A/B testing and experimental design and quantitative benchmarks for model improvement 
  • Apply data privacy and compliance rules under regulations like GDPR, CCPA. Apply ethical AI principles. Apply model fairness and bias mitigation techniques. 
  • Conduct analyses to assess model performance and campaign performance, both against test datasets and actual results once deployed. 
  • Forecast campaign results based on models built and validate forecast against actuals. 
  • Work with marketing data architects and engineers to ensure data is clean, complete, correct, and suitable for modeling using AI/ML platforms. 
  • Develop and maintain data pipelines. Implement feature engineering techniques. Find, recommend, and purchase additional data to use in model building 
  • Proactively identify opportunities for model improvement and need for additional modeling projects. 
  • Maintain clear and organized documentation of data, methodologies, and results. 
  • Implement automation in existing processes to improve overall efficiency. 
  • Perform ad hoc analysis to support Marketing Distribution efforts 
  • Actively seek out innovation and optimization use cases and experiments that will result in organizational transformation and sales and profit improvements. 

Qualifications

Basic Required Qualifications:

  • Skilled in cross-functional collaboration, agile methodologies, project management and stakeholder communication. 
  • Advanced training or academic focus in non-parametric statistics, resampling methods, or Bayesian approaches for small sample inference 
  • Experience applying sequential testing or multi-armed bandit approaches to maximize insights from limited samples in marketing contexts 
  • Able to effectively communicate and translate complex, technical finding in a candid, clear, concise, and non-technical fashion to all audiences 
  • Maintain perspective between the big picture and the tactical details. Remains aligned with the organization’s strategic plan. 
  • Stellar attention to detail, including maintaining accuracy and consistency across a suite of data science assets, keeping documentation up to date, and proactively identifying and addressing any quality concerns. 
  • Self-starter with the ability to identify priorities and focus on items with high business impact.
  • Ability to present complex analytical findings with persuasiveness and succinctness.

Preferred Qualifications:

  • Master’s degree in Statistics, Economics, Mathematics, Data Science, or related field. Experienced in marketing analytics or customer behavior modeling.  
  • 5 to 7 years of experience in data science, including hands-on experience with Machine Learning (e.g., scikit-learn, TensorFlow, PyTorch, DataRobot, Databricks) and Generative Artificial Intelligence. Experience with automated model deployment and monitoring tools. 
  • Possess outstanding analytical, modeling, problem-solving, and critical-thinking skills. 
  • Experienced with cloud platforms such as AWS, Azure, and Google Cloud. Familiar with big data technologies (Spark, Hadoop) 
  • Strong knowledge of machine learning algorithms and their applications in automated systems. Experience with advanced modeling techniques like ensemble methods, time series analysis, and probabilistic modeling 
  • High proficiency in Python or R for statistical analysis, model development, and process automation. Proficient+ with SQL for data extraction and manipulation.  
  • Proficiency with data visualization tools (Power BI, Tableau, or similar) and their automation capabilities

While performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel, talk, hear and concentrate. Specific vision abilities required by this job include close vision, distance vision, depth perception, and ability to adjust focus.

This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements. Reasonable accommodation will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.

We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.

AAA Life Insurance Company does not offer immigration sponsorship for this position. This includes visa types such as H-1B, TN, and STEM OPT. Please do not apply if you currently require or may require employer-sponsored immigration support now or in the future.

#LI-Hybrid