Predictive Modeling, Risk Scientist

🕒 May 18

🏛️ District of Columbia, Florida, +4 more states – Remote

🏛️ District of Columbia – Remote 🐊 Florida – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote

💵 $128k - $185k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🎲 Risk

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Cover Whale

WebsiteLinkedInAll Job Openings

51 - 200 employees

🚗 Transport

☁️ SaaS

Insurance • Transport • SaaS

Cover Whale is a provider of commercial auto insurance products specifically designed for truckers in the United States. The company offers a range of insurance options including auto liability, motor truck cargo, auto physical damage, non-trucking liability, and truckers’ general liability, aiming to provide better and more affordable coverage for America's truckers. Cover Whale leverages its industry-leading telematics and real-time safety coaching to improve driver safety, offering premium discounts for safe driving. Its innovative platform allows agents to obtain instant policy quotes and benefits from same-day binding, enhancing productivity and efficiency. The company emphasizes safety and technology, aiming to reshape the commercial trucking insurance sector.

📋 Description

• 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.

🎯 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.

🏖️ 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