Data Scientist Manager

Genworth Financial • Richmond, VA

44d • Hybrid

About The Position

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 careers by learning from the world and each other.

Requirements

• Bachelor’s degree in an analytical, quantitative, or technical discipline
• 5+ years business analytics and business support functions experience
• 5+ years of experience in one or more of the following statistical / analytic languages such as Python (Pandas, Scikit-Learn), Apache Spark (or PySpark), Hive, and Scala in a cloud computing environment
• 5+ years of experience in one or more of the following: database query and management tools (SQL, Spark, Preseto/Athena/Hive / HQL etc.)
• Hands-on experience with advanced analytics like logistic regression, time series, forecasting, optimization, and other predictive modeling techniques. ML experience and knowledge of ML platforms, libraries and programming
• Experience using GLMs, XGBoost and other predictive analytic techniques
• Ability to translate business needs into technical requirements and articulate analytic solution to get business buy-in
• Ability to influence decision makers and drive consensus

Nice To Haves

• Master’s degree in a quantitative or related field
• Experience with Long‑Term Care Insurance products, claims processes, or actuarial environments
• Experience with ETL, data engineering concepts, or RDBMS systems (SQL Server, Oracle, Greenplum)
• Experience with big data ecosystems (Hadoop, Spark, Hive, Databricks, AWS/Azure)
• Background in advanced modeling techniques, MLOps, or deployment frameworks

Responsibilities

• Lead complex, cross‑functional analytics initiatives from concept through execution, ensuring insights drive business strategy.
• Partner with senior leaders to define analytical problem statements, gather requirements, and translate business needs into data‑driven solutions.
• Act as a thought leader for data science best practices, analytic design, and modeling approaches across the organization.
• Influence stakeholders at all levels, presenting insights, 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 projects, including cloud transitions, data engineering collaboration, and scalable data architecture improvements.
• Ensure data quality, model documentation, reproducibility, and governance standards are met.
• Communicate complex analytical findings through compelling written, visual, and verbal storytelling.
• Deliver clear, concise presentations that enable senior leaders to make informed decisions rapidly.

Benefits

• Competitive Compensation & Total Rewards Incentives
• Comprehensive Healthcare Coverage
• Multiple 401(k) Savings Plan Options
• Auto Enrollment in Employer-Directed Retirement Account Feature (100% employer-funded!)
• Generous Paid Time Off – Including 12 Paid Holidays, Volunteer Time Off and Paid Family Leave
• Disability, Life, and Long Term Care Insurance
• Tuition Reimbursement, Student Loan Repayment and Training & Certification Support
• Wellness support including gym membership reimbursement and Employee Assistance Program resources (work/life support, financial & legal management)
• Caregiver and Mental Health Support Services

What This Job Offers

• Job Type: Full-time
• Career Level: Manager