Predictive Modeling & Risk Scientist

Cover Whale•Orlando, FL

3d•$128,000 - $192,000

About The Position

Cover Whale is the nation’s leading commercial trucking insurtech. We improve road safety by combining the insurance products we sell with our telematics-based, data-driven driver coaching and safety program known as DriveSmart. Our program is proven to save lives while delivering better insurance for our drivers. For more information, please visit www.coverwhale.com. Join us in the mission! The Role: We are seeking a highly analytical, technically strong Actuarial/Data Science professional to own and evolve our end-to-end reserving and predictive modeling capabilities. This role will maintain and enhance our Python-based reserving models while building predictive models using live telematics and claims data to drive pricing, cancellation strategy, and large loss detection. The position sits at the core of our underwriting and growth strategy, directly influencing dynamic pricing, loss ratio performance, and profitable expansion. This is a very exciting and high-impact job that involves a lot of thinking, research, and creativity.

Requirements

Experience with insurance analytics, actuarial modeling, or predictive risk modeling in the insurance industry.
Strong proficiency in Python for statistical modeling and data analysis.
Comfortable leveraging AI-assisted coding tools (Claude, Copilot, etc.) while critically validating outputs.
Experience working with large-scale datasets and building production-grade analytical models.
Demonstrated experience with actuarial reserving models or insurance forecasting methodologies.
Experience applying machine learning techniques such as regression models, gradient boosting, classification models, or anomaly detection.
Ability to design models that influence pricing, underwriting decisions, and portfolio risk management.
Strong SQL and data manipulation skills.
Experience building automated analytical pipelines or reporting workflows.
Curious, hard-working, thinking outside of the box, creative, attention to detail, and use of Claude code.

Nice To Haves

Actuary
Mathematics
Big Four consulting experience.

Responsibilities

Own and continuously improve the end-to-end reserving process, including maintaining and enhancing Python-based reserving models to improve accuracy and efficiency.
Develop and deploy predictive models using telematics, claims, and policy data to improve pre-bind and post-bind risk selection, with measurable impact on ULR and cancellation performance.
Build and refine large loss models using claims notes and historical data to improve early identification of high-risk claims.
Design and implement dynamic pricing frameworks and capabilities leveraging live market and portfolio data.
Translate complex data insights into clear actionable business recommendations for underwriting, growth, and leadership teams.
Produce carrier-level reporting deliverables and analytical outputs that meet high-quality and compliance standards.
Create agency-level and geographic performance insights to guide growth strategy and strategic initiatives.
Automate recurring analyses and reporting workflows to increase speed, scalability, and reliability.