Hybrid Predictive Modeler - Analytics & ML

aoins; Lansing (MI); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Matched 401(k)

Fully-funded pension plan

Bonus programs

Student loan assistance

Gym cost reimbursement

Generous PTO

Education & training programs

Job summary

Auto-Owners Insurance is seeking a Predictive Modeler to join our analytics teams in a hybrid role. After initial in-person training, the position may allow up to 3 days per week working from home, though we are not offering fully remote positions.

You will build models using statistical or machine learning methods, work with large datasets, and present results to stakeholders with clear visuals. Documentation and monitoring of model performance are essential.

Qualifications

• Bachelor’s degree in a quantitative discipline or equivalent experience.
• Strong problem-solving and critical thinking skills.
• Familiarity with statistical modeling or data science concepts (clustering, regression, classification).

Responsibilities

• Use statistical or machine learning techniques to build models addressing business needs and regulatory requirements.
• Work with large, complex data sets and learn Auto-Owners data structures and metrics.
• Conduct ad-hoc analyses and present results to stakeholders with clear visualizations.
• Create clear, understandable documentation for models.
• Monitor model performance and implement iterative improvements.

Skills

Statistical modeling

Data science concepts

Problem solving

Teamwork

Communication

Education

Bachelor’s degree in quantitative discipline

Tools

Python

R

SQL

Job description

Auto-Owners Insurance is seeking a Predictive Modeler to join our analytics teams in a hybrid role. After initial in-person training, the position may allow up to 3 days per week working from home, though we are not offering fully remote positions.

You will build models using statistical or machine learning methods, work with large datasets, and present results to stakeholders with clear visuals. Documentation and monitoring of model performance are essential.