Predictive Modeling & Risk Scientist
Cover Whale
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New York, NY
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Mid-Senior level
Posted March 30, 2026
4 variants
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Responsibilities
Commitments
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 Please note: Applicants must be authorized to work for ANY employer in the U.S.
Commitments
Automate recurring analyses and reporting workflows to increase speed, scalability, and reliability Please note: Applicants must be authorized to work for ANY employer in the U.S.
We are unable to sponsor or take over sponsorship of an employment Visa at this time.
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.
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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 Soft skills: Curious, hard-working, thinking outside of the box, creative, attention to detail, and use of Claude code.
- Candidates advancing through the interview process may be asked to complete a brief work exercise related to predictive modeling and risk analysis.
Preferred Skills
- Demonstrated experience with actuarial reserving models or insurance forecasting methodologies
- 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.
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 Please note: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
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 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.
Benefits
Compensation : The Expected base pay for the role will be $128,000 - $185,000 at the commencement of employment. However, base pay if hired will be determined on an individualized basis and depends on the geographical location, years of experience, etc. 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
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 Please note: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
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 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.
Benefits
Compensation : The Expected base pay for the role will be $128,000 - $185,000 at the commencement of employment. However, base pay if hired will be determined on an individualized basis and depends on the geographical location, years of experience, etc. 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