Lead Risk Analytics Data Scientist

Role Overview

Lead Risk Analytics Data Scientist at Extend (full remote). You’ll lead risk monitoring and analytics work that supports underwriting, claims initiatives, and premium setting to maintain a healthy loss ratio. You’ll also take ownership of the Risk Analytics data architecture and build tooling that informs key business decisions.

Key Missions

• Collaborate with cross-functional teams to maintain a healthy loss ratio via premium changes, underwriting process improvements, and claims initiatives.
• Own the Risk Analytics data architecture: design data models, define standards, and shape how the function operates long-term.
• Build decision-support tooling for claims initiatives, premium adjustments, and program renegotiations; provide recommendations to senior leadership.

Responsibilities

• Develop and maintain data pipelines and modeling workflows.
• Translate deep analytical findings into clear insights for both technical and non-technical audiences.
• Partner with teams beyond insurance to prioritize what’s best for the business holistically.

Requirements

• Strong analytical/data skills including SQL plus Python or R.
• Experience with pipeline development and data modeling (e.g., dbt, Snowflake).
• Proficiency with visualization tools such as Tableau or Streamlit.
• 5+ years experience in actuarial pricing, predictive modeling, or related Risk Analytics.
• Ability to communicate insights effectively across audiences.
• Empathy, humility, and curiosity.
• Interest in and excitement about using new AI tools to improve day-to-day efficiency.

Nice-to-Haves

• Relevant Actuarial experience (e.g., ACAS or equivalent exam progress).
• Bachelor’s degree in Actuarial Science, Mathematics, Statistics, or a related field.