Vice President, Applied AI Science for EB, Ops, and Customer

VP Data Science - GD04AE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future. Nimbus Data Systems is hiring a Vice President, Applied AI - Employee Benefits & Operations to define and lead the next generation of AI-driven transformation across the business. This role is responsible for driving Applied AI and Data Science strategy, execution, and governance across enrollment, billing, customer service, and operational functions, delivering measurable improvements in growth, efficiency, accuracy, and customer experience. The leader will oversee a diverse portfolio of Machine Learning, Generative AI, Agentic AI, and predictive analytics solutions while influencing enterprise AI strategy, championing responsible AI practices, and building organizational capability to accelerate Nimbus Data Systems's AI-powered future. This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office locations (Hartford, CT; Chicago, IL; Columbus, OH; Charlotte, NC) will have the expectation of working in an office 3 days a week. Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be eligible to work in the US without company sponsorship. Primary Job Responsibilities Own Applied AI strategy and integrated data science outcomes across Employee Benefits and Operations, including employer lifecycle, enrollment, billing, service delivery, and operational functions, ensuring alignment to enterprise AI priorities while tailoring execution to domain-specific needs. Define domain-level Applied AI strategy and influence enterprise AI direction through evidence-based recommendations, technical insight, and cross-functional alignment. Lead executive decision-making across supported lines of business, driving trade-offs across quality, risk, cost, scalability, and time-to-value for Applied AI and data science initiatives. Drive transformation of Employee Benefits and Operations processes through Applied AI and data science, including enrollment optimization, service automation, contact center intelligence, billing accuracy, and employer/member experience across the full lifecycle. Lead application and execution of the enterprise Applied AI operating model within domain scope, ensuring teams effectively operate within defined decision rights, engagement models, and delivery governance across multiple portfolios. Ensure consistent adherence to enterprise AI governance frameworks across portfolios, including application of evaluation, monitoring, model risk management, and responsible AI practices in alignment with enterprise standards and regulatory expectations. Set direction for evaluation and performance measurement across solutions, spanning generative and agentic AI, retrieval-augmented systems, and traditional models including persistency, enrollment forecasting, service demand prediction, billing accuracy, and operational performance optimization. Oversee end-to-end Applied AI and data science lifecycle across portfolios, from problem framing through model development, validation, deployment, monitoring, and continuous improvement. Lead the identification and integration of new data sources, AI tooling, and quantitative methods into Employee Benefits and Operations workflows, improving service delivery, accuracy, scalability, and cost efficiency. Oversee domain-level AI risk posture and model governance, ensuring alignment with Legal, Compliance, Model Risk, Privacy, Security, and Audit partners and maintaining readiness for regulatory review. Drive cross-line of business prioritization, investment planning, and workforce strategy, aligning initiatives to measurable business outcomes and capacity constraints. Champion reuse, standardization, and componentization of Applied AI and data science assets, ensuring alignment with enterprise AI platform strategy and enabling scalable deployment across portfolios. Partner with Employee Benefits, Operations, Technology, and Service leaders to embed Applied AI into employer onboarding, enrollment, billing, service, and operational strategies. Design and scale the Applied AI leadership system across supported lines of business, including succession pipelines, capability frameworks, and long-term talent architecture. Define and lead a domain-level Applied AI research and innovation agenda, balancing near-term delivery with exploration of emerging techniques, tools, and capabilities. Monitor external AI, healthcare benefits, and regulatory trends (e.g., HIPAA, ERISA, data privacy), industry practices, and competitor capabilities to maintain competitive positioning and inform strategic direction. Skills Demonstrated ability to lead Applied AI and dat