Senior Data Scientist

Location(s)

Details

Kemper is one of the nations leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture valuable opportunities for personal development and professional challenge and a healthy work-life balance can be highly motivating and productive. Kempers products and services are making a real difference to our customers who have unique and evolving needs. By joining our team you are helping to provide an experience to our stakeholders that delivers on our promises.

Position Summary:

Data Science is a driver of significant competitive advantage for Kemper and is critical to the organizations success. As a member of the Kemper Auto Data Science team this position is responsible for independently designing developing implementing and monitoring predictive modeling and analytical solutions that support pricing segmentation product development and profitable growth.

Position Responsibilities:

• Independently designs develops validates and implements statistical and machine-learning solutions for complex business problems.
• Owns significant analytical and modeling workstreams from problem definition through delivery and performance monitoring.
• Collaborates with data scientists data engineers and business partners to develop scalable analytical solutions.
• Develops reusable well-documented analytical workflows using modern data science and cloud technologies.
• Manages priorities deliverables and timelines for assigned projects and communicates progress risks results and recommendations to stakeholders.
• Participates in model and code reviews and recommends methodological or implementation enhancements.
• Provides technical guidance to less experienced team members and contributes to data science best practices.

Position Qualifications:

Minimum Job Requirements

• Bachelors degree in Mathematics Statistics Engineering or another STEM field with at least 8 years of relevant experience or a graduate degree in a STEM field with at least 6 years of relevant experience in the insurance industry data science/analytics or a related environment. PhD in a STEM field preferred with at least 4 years of relevant industry experience
• At least 4 years of firsthand experience with statistical modeling and AI/ML platforms
• Demonstrated experience independently developing and delivering statistical or machine-learning solutions

Required Job Skills

• Strong proficiency in Python including experience with common data science libraries such as pandas NumPy scikit-learn SciPy and visualization libraries.
• Strong proficiency in SQL for data extraction transformation validation and analysis of large and complex datasets.
• Strong understanding of statistical modeling and machine learning concepts including model design feature development training validation performance evaluation interpretation and monitoring.
• Hands-on experience with a range of statistical and machine learning techniques such as generalized linear models regularized regression tree-based models ensemble methods clustering or neural networks.
• Ability to develop readable maintainable modular and well-documented Python code and reusable analytical workflows.
• Experience working with large and complex structured datasets from relational databases delimited files data frames and other common data formats.
• Strong problem-solving skills with the ability to independently develop analytical approaches for complex or ambiguous business problems.
• Excellent communication skills particularly the ability to translate technical methodologies results and recommendations for both technical and business audiences.
• Ability to independently manage significant analytical workstreams while collaborating effectively with data scientists data engineers and business partners.
• Experience participating in model reviews code reviews and technical discussions and providing constructive recommendations for improvement.

Preferred Qualifications

• Prior experience in insurance financial services pricing risk modeling or a related analytical business environment.
• Experience applying predictive modeling techniques to pricing risk product or other complex business applications.
• Experience with Git GitLab or other version control and collaborative development tools.
• Hands-on experience with cloud platforms such as AWS Azure Databricks or similar environments for data science and machine learning workflows.
• Familiarity with MLOps practices such as model packaging CI/CD workflows reproducible pipelines model deployment and performance monitoring.
• Experience developing reusable or modular analytical frameworks that support scalable model development and implementation.
• Experience providing technical guidance or mentoring to less experienced data scientists.

Additional Information

• This position can be worked in a hybrid arrangement from a local Kemper office. Remote options are available for non-local candidates.
• The range for this position is $104300 to $173300. When determining candidate offers we consider experience skills education certifications and geographic location among other factors. This job is eligible for an annual discretionary bonus and Kemper benefits (Medical Dental Vision PTO 401k etc.)
• Sponsorship is not accepted for this opportunity.

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