Predictive Modeling & Risk Scientist at Cover Whale

Washington, District of Columbia, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Jun, 26

Salary

192000.0

Posted On

15 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Reserving Models, Predictive Modeling, Python, Telematics Data, Claims Data, Pricing Strategy, Risk Selection, Large Loss Detection, Machine Learning, SQL, Data Analysis, Actuarial Modeling, Forecasting Methodologies, Risk Management, Data Visualization, Workflow Automation

Industry

Insurance

Description

Who is Cover Whale? 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. 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. 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. Soft skills: Curious, hard-working, thinking outside of the box, creative, attention to detail, and use of Claude code. Preferred Qualifications: Actuary, Mathematics, Big Four consulting experience. Candidates advancing through the interview process may be asked to complete a brief work exercise related to predictive modeling and risk analysis. The exercise is designed to reflect real-world challenges relevant to the role. Candidates completing this step will receive reasonable compensation for their time. Compensation: The Expected base pay for the role will be $128,000 - $192,000 at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include discretionary bonus and other Cover Whale-sponsored total rewards/benefits. Perks/Benefits: Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k) match Wellness benefits, including EAP, Gym Reimbursement, etc. Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Paid Family Leave (Maternity, Paternity) Tuition Assistance Professional Training & Development

Responsibilities

This role involves owning and continuously improving the end-to-end reserving process, including maintaining and enhancing Python-based reserving models for accuracy and efficiency. The professional will also develop and deploy predictive models using telematics, claims, and policy data to enhance risk selection and influence dynamic pricing strategies.