Data Scientist Manager

At Genworth, we empower families to navigate the aging journey with confidence. We are compassionate, experienced allies for those navigating care with guidance, products, and services that meet families where they are. Further, we are the spouses, children, siblings, friends, and neighbors of those that need care—and we bring those experiences with us to work in serving our millions of policyholders each day. We apply that same compassion and empathy as we work with each other and our local communities. Genworth values all perspectives, characteristics, and experiences so that employees can bring their full, authentic selves to work to help each other and our company succeed. We celebrate our diversity and understand that being intentional about inclusion is the only way to create a sense of belonging for all associates. We also invest in the vitality of our local communities through grants from the Genworth Foundation, event sponsorships, and employee volunteerism. Our four values guide our strategy, our decisions, and our interactions: Make it human. We care about the people that make up our customers, colleagues, and communities. Make it about others. We do what's best for our customers and collaborate to drive progress. Make it happen. We work with intention toward a common purpose and forge ways forward together. Make it better. We create fulfilling purpose-driven c [... source excerpt omitted ...] sin. YOUR ROLE As a Data Scientist Manager, you serve as both a strategic thought partner and a technical expert driving advanced analytics capabilities across the organization. You will lead complex, high‑impact initiatives and partner closely with senior leaders to embed data‑driven insights into business strategy. This role combines deep analytical expertise with advanced modeling. You will influence decision‑making, develop scalable data products, and elevate the organization’s analytic maturity in support of Long‑Term Care Insurance strategy. What you will be doing Lead complex, cross‑functional analytics initiatives from concept through execution, ensuring insights dri [... source excerpt omitted ...] nsights, use cases, and strategic recommendations. Develop and deploy advanced statistical models, machine‑learning tools, and predictive capabilities supporting LTC strategy and customer insights Conduct deep exploratory data analysis to uncover trends, relationships, and emerging insights that drive strategic action. Design and implement repeatable analytics pipelines, feature engineering strategies, and model validation frameworks. Build advanced datasets and analytical assets using SQL/SAS/Python/R; explore large, complex data environments. Develop subject‑matter expertise in policies, claims, customer behavior, and LTC data ecosystems. Contribute to data modernization