Build predictive models and applied LLMs designed to support the Kemper claims operation in areas such as fraud detection, subrogation identification, vehicle damage severity, adjuster triage and claims quality management
Develop and automate predictive modeling processes that can be deployed through the organization to solve recurring analytics needs
Contribute to the improvement of internal modeling capabilities and data infrastructure by suggesting and applying tweaks to existing processes
Monitor deployed solutions and escalate as needed

Proficient in Python programming language (scikit-learn, pandas, numpy, scipy, etc.)
Proficiency with several modeling techniques such as generalized linear models, decision trees, ensemble learning, regularized models (ridge/lasso/nets), clustering, and neural networks
Prior experience working with AWS is a plus
Some experience with natural language processing is preferred
Some experience working with LLMs via API is preferred but not required
Excellent overall communication skills, especially the ability to translate technical results for non-technical audiences
Graduate degree required in a quantitative field: Mathematics, Statistics, CS, Physics, MIS, Economics, Electrical Engineering, etc.
2+ years’ experience in a data science/predictive analytics environment preferred

Data Scientist

Key skills