Director-Data Science (New York, NY)
About The Position
The Director, Data Science, Global Servicing Decision Science leads the vision, strategy, and execution of Decision Science across Global Servicing. The role translates complex customer and business challenges into scalable intelligence capabilities that improve customer experience, colleague effectiveness, operational efficiency, membership value, and controls. It leads a high-performing data science team and partners across Global Servicing and the enterprise to embed intelligent decisioning into servicing experiences and processes. The Director provides technical and strategic leadership across AI/ML, GenAI, prediction, recommendation, optimization, experimentation, and learning. The role advances capabilities such as Agentic AI, transformer-based recommendation systems, and Conversational AI while ensuring solutions are production-ready, measurable, governed, and continuously improving. It oversees reusable production data science products and decisioning systems, shapes the technical roadmap, and drives adoption and measurable business impact through cross-functional leadership.
Requirements
- Bachelor’s degree in a quantitative field such as Engineering, Computer Science, Mathematics, Statistics, or Economics.
- Exceptional analytical and conceptual problem-solving ability, including structuring and solving complex, ambiguous business challenges using first-principles thinking.
- Proven experience leading and developing high-performing analytics or data science teams in complex, cross-functional environments.
- Strong technical foundation in modern data science and AI, with the ability to guide solution design, challenge technical approaches, and connect analytical choices to business outcomes.
- Ability to influence senior stakeholders through clear, structured, compelling communication and executive storytelling.
- Experience driving large-scale analytics, Decision Science, or AI initiatives from concept through production, adoption, and ongoing optimization.
- Strong commercial acumen and storytelling, connecting technical strategy, architecture, and investment choices to measurable business value.
Nice To Haves
- Master’s degree in a quantitative field such as Engineering, Computer Science, Mathematics, Statistics, or Economics.
- Technical exposure to or experience driving Agentic AI and agentic workflows, transformer architectures and transformer-based recommendation systems, Conversational AI, LLMs, and advanced personalization or next-best-action systems.
- Strong understanding of the end-to-end Decision Science and AI lifecycle, including experimentation, model/AI evaluation, decision logic and orchestration, productionization, monitoring, governance, and continuous optimization.
- Track record of building scalable data products, recommendation or decisioning systems, or AI-driven capabilities with measurable customer, revenue, productivity, cost, or control outcomes.
- Experience driving transformation from traditional analytics toward AI-powered, productized Decision Science capabilities and reusable enterprise solutions.
Responsibilities
- Define and lead the Decision Science roadmap across Global Servicing, prioritizing opportunities in servicing experiences, membership value and engagement, colleague efficiency, and operational excellence.
- Translate business strategy into Decision Science priorities, success measures, and investment choices tied to customer and business outcomes.
- Provide technical leadership across AI/ML, GenAI, prediction, recommendation, optimization, experimentation, and learning, setting standards for solution design, evaluation, and analytical rigor.
- Advance Agentic AI and multi-agent workflows, transformer-based recommenders and representation learning, and Conversational AI/LLM-based systems for intelligent servicing decisions.
- Challenge architectures, modeling choices, evaluation frameworks, and trade-offs, and guide teams from experimentation through scalable production deployment.
- Oversee development of reusable, production-ready data science products and decisioning systems using customer, behavioral, contextual, and operational data.
- Partner with Technology, platform, and governance teams to deploy and evolve AI solutions with suitable architecture, observability, controls, model and AI quality, and lifecycle discipline.
- Lead, mentor, and grow a high-performing data science team, fostering technical excellence, first-principles problem solving, innovation, ownership, and commercial judgment.
- Build organizational capabilities in Applied GenAI, AI engineering and architecture, advanced recommendation and decisioning methods, strategic problem solving, and commercial storytelling.
- Influence senior stakeholders and build cross-functional accountability to drive prioritization, investment decisions, adoption, and execution of major initiatives.
- Evaluate advances in AI and Decision Science and translate relevant methods into practical, scalable capabilities and reusable best practices.
- Shape a forward-looking technical roadmap for Agentic AI, Conversational AI, modern recommendation systems, experimentation, AI engineering, architecture, governance, and continuous optimization.
Benefits
- Competitive base salaries
- Bonus incentives
- 6% company match on retirement savings plan
- Free financial coaching and financial well-being support
- Comprehensive medical, dental, vision, life insurance, and disability benefits
- Flexible working model with hybrid, onsite, or virtual arrangements depending on role and business need
- 20+ weeks paid parental leave for all parents, including for pregnancy, adoption, or surrogacy
- Free access to global on-site wellness centers staffed with nurses and doctors, depending on location
- Free and confidential counseling support through the Healthy Minds program
- Career development and training opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Director
