Senior Actuarial Data Scientist (hybrid)

American Family Insurance

Base: $113,000.00 - $194,000.00; bonus/equity: ann...
Hybrid
Python programming proficiency
Glm/gbm model deployment
Large complex dataset analysis
American Family Insurance is seeking a Senior Actuarial Data Scientist to develop predictive modeling solutions within their Property & Casualty Actuarial team. The ideal candidate will possess strong programming skills in Python, experience deploying predictive models, and a solid background in statistical analysis

Job Summary

  • The role involves developing scalable analytics and predictive modeling solutions to drive business decisions within the Property & Casualty Actuarial team.
  • Candidates will combine strong business acumen with advanced quantitative methods and modern software engineering practices to deliver production-ready solutions.
  • The company offers comprehensive benefits including medical, dental, vision, a competitive 401(k), pension plan, and paid time off.

Matching Summary

Match Score: 85

American Family Insurance is seeking a Senior Actuarial Data Scientist to develop predictive modeling solutions within their Property & Casualty Actuarial team. The ideal candidate will possess strong programming skills in Python, experience deploying predictive models, and a solid background in statistical analysis.

Salary

Base: $113,000.00 - $194,000.00; Bonus/Equity: Annual incentive included; Benefits: Medical, dental, vision, 401(k), pension, PTO

Skills & Requirements

Must-have

  • Python programming proficiency
  • GLM/GBM model deployment
  • Large complex dataset analysis
  • Statistical modeling techniques
  • Source control and testing frameworks

Nice-to-have

  • Business acumen in actuarial domain
  • Innovative problem-solving approach
  • Cross-departmental collaboration skills
  • Big data technology experience

Key Requirements

  • Deployed predictive models in production
  • Advanced Python programming skills
  • Experience with AI/ML solution design
  • Software development best practices knowledge

Work Rights

Not specified

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