Senior Actuarial Data Scientist (FCAS) – Pricing Lead

Munich Reinsurance America, Inc; Bremen (OH); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Dental insurance

Life insurance

Paid time off

401(k)

Job summary

American Modern Insurance Group, Inc., a Munich Re company, is seeking a Principal Data Scientist to lead end-to-end pricing models for personal lines and guide analytics strategy. The role blends advanced modeling, regulatory responsibilities, and cross-team collaboration in a hybrid environment.

The senior technical leader will mentor junior staff, influence enterprise predictive initiatives, and contribute to broader decision science efforts beyond pricing.

Qualifications

• Six or more years of data science/predictive analytics experience in insurance or eight+ years in another industry.
• Independently build models and analyses and communicate results to partners.
• Experience with regulatory filings and modeling practices; mentorship of juniors.

Responsibilities

• Lead pricing model strategy for a subset of products.
• Develop, deploy, monitor, and maintain predictive models.
• Collaborate with stakeholders to align modeling with business needs.
• Manage filing schedules for aligned products.
• Present predictive analytics results to internal and external customers and management.
• Mentor junior data scientists and teammates.

Skills

FCAS

R

Python

GLMs/GBMs

AI/ML concepts

Databricks

Data structures

Agile methodologies

Testing & validation

Project management

Education

Master's degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and related major

Tools

Databricks

Job description

American Modern Insurance Group, Inc., a Munich Re company, is seeking a Principal Data Scientist to lead end-to-end pricing models for personal lines and guide analytics strategy. The role blends advanced modeling, regulatory responsibilities, and cross-team collaboration in a hybrid environment.

The senior technical leader will mentor junior staff, influence enterprise predictive initiatives, and contribute to broader decision science efforts beyond pricing.