Senior Manager - Data Science; Pricing & Underwriting; Remote

Data Science Leader

Help shape smarter pricing and underwriting decisions through trusted, explainable data science. In this role, you will lead a team that builds and advances predictive models used to estimate healthcare renewal risk. You will combine people leadership, technical expertise, and strong business partnership to deliver scalable solutions that improve decision quality across a complex client portfolio.

• Lead, coach, and develop a team of Data Scientists while building a culture of learning, collaboration, technical excellence, and innovation.
• Guide the strategy and long-term evolution of renewal risk estimation capabilities, including a flagship renewal risk model and related analytics.
• Set priorities and allocate resources across a portfolio of high-impact data science initiatives to deliver reliable business outcomes.
• Provide hands-on technical direction for solution design, predictive modeling, machine learning, statistical analysis, forecasting, model evaluation, and risk estimation.
• Establish practical standards for peer review, documentation, validation, monitoring, performance tracking, governance, and ongoing model maintenance.
• Improve model performance, explainability, reproducibility, reliability, and business relevance while meeting enterprise standards.
• Partner with pricing, underwriting, actuarial, data, technology, and analytics teams to turn business needs into clear analytical roadmaps and production-ready solutions.
• Communicate model outputs, assumptions, limitations, and recommendations in a clear way for technical and non-technical audiences.
• Support adoption of analytical solutions by helping stakeholders understand how to use model insights in pricing and underwriting workflows.

• 8+ years of experience in data science, advanced analytics, statistical modeling, machine learning, actuarial analytics, or a related quantitative field.
• Experience developing predictive models, machine learning solutions, and advanced analytical methods using large, complex datasets.
• Experience leading Data Scientists and delivering complex analytical initiatives that solve business problems and influence decisions.
• Strong knowledge of statistical modeling, predictive analytics, machine learning, model evaluation, and experimental design.
• Proficiency with modern data science technologies such as Python, SQL, Spark, and machine learning frameworks.
• Experience developing, validating, monitoring, and governing analytical models in production environments.
• Strong communication and stakeholder management skills, including the ability to explain complex concepts to varied audiences.
• Ability to balance strategic leadership with hands-on technical contribution.

• Bachelor's or advanced degree in Statistics, Data Science, Mathematics, Computer Science, Economics, Operations Research, Engineering, or a related quantitative field.
• Experience with healthcare data, including medical claims, pharmacy claims, eligibility, provider, consumer, or related datasets.
• Experience supporting pricing, underwriting, risk assessment, forecasting, or related business functions.
• Experience deploying and supporting machine learning solutions in production.
• Experience leading cross-functional work across business, analytics, and technology teams.
• Familiarity with responsible AI, model governance, and explainability practices.