Data Scientist, Underwriting Analytics (Hybrid/Remote)

usaa; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

USAA is seeking a Data Scientist to join the P&C Underwriting Data Science team. The role focuses on analyzing data, prototyping models, and deploying data science products in operations.

The candidate will work across data engineering and IT to deliver production-ready analytics in a hybrid work setting from one of several US locations. The position requires strong ML, statistical skills, and experience with Python, SQL, and data workflows.

Qualifications

• Bachelor's degree or four years of relevant education/experience in quantitative field.
• Four years of experience in predictive analytics or data analysis; advanced degree may substitute for experience.
• Two years of experience in training and validating statistical or ML models.
• Two years of experience in one or more dynamic scripting languages (Python, R) for statistics or ML.

Responsibilities

• Gathers, interprets, and processes structured and unstructured data for analytics.
• Develops scalable ML, simulation, and optimization solutions to deliver insights and value.
• Selects modeling techniques considering data constraints and business needs.
• Deploys models within MDC and MRM frameworks and documents processes.

Skills

Statistical analysis

Machine learning

Python

SQL

Education

Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial science, science, engineering, or quantitative field

Advanced degree (Master's/PhD) in quantitative field

Tools

Python

R

SQL

HQL

NoSQL

Job description

USAA is seeking a Data Scientist to join the P&C Underwriting Data Science team. The role focuses on analyzing data, prototyping models, and deploying data science products in operations.

The candidate will work across data engineering and IT to deliver production-ready analytics in a hybrid work setting from one of several US locations. The position requires strong ML, statistical skills, and experience with Python, SQL, and data workflows.