Data Scientist

A career at Auto-Owners is challenging and rewarding.  Our group of caring associates create financial security by helping individuals and businesses make a new start when a loss occurs.

Auto-Owners Insurance, a top-rated insurance carrier, is seeking a data scientist to join our analytics teams. The position requires the person to:

• Use statistical and machine learning techniques to build models that address business needs and comply with regulatory requirements
• Work with large, complex data sets and develop a comprehensive knowledge of Auto-Owners data structures and metrics
• Conduct ad-hoc analysis and present results clearly at multiple-levels of stakeholders through visual displays of quantitative information
• Design, prototype, and implement new approaches for solving problems. 
• Collaborate with a cross-functional team, including software developers, architects, and business leaders
• Create clear and easy to understand documentation for models
• Monitor model performance and implement iterative improvements

• Master’s degree in a quantitative discipline (e.g. Mathematics, Statistics, Computer Science, Physics, Operations Research, Economics, Electrical Engineering, etc.)
• Proficiency in SQL or other data querying language
• An understanding of statistical and machine learning techniques, including classification, regression, clustering, feature engineering, decision trees, gradient boosting, deep learning, etc.
• Experience with common data science toolkits, such as R, Python, TensorFlow, SQL, Scikit-learn, Keras, etc.
• Aptitude and willingness to learn new things and teach others
• Strong written and oral communication skills
• 2-4 years of professional experience building models with large data sets. Candidates with 0-1 years of experience, please use the job posting for “Predictive Modeler”.
• (Preferred) PhD in a quantitative discipline
• (Preferred) Experience in the insurance industry

Auto-Owners Insurance is an equal opportunity employer. The Company hires, transfers, and promotes on the basis of ability, without consideration of disability, age, sex, race, color, religion, height, weight, marital status, sexual orientation, gender identity or national origin, or any factor contrary to federal, state or local law.