Senior Manager, Data Science

Core Responsibilities:

• Manages a team of data scientists handling diagnostic, predictive, and prescriptive analytics projects to support data‑driven decision‑making. Continuously evolves Vanguard's data science capabilities with rapid prototyping and MVPs to shorten time‑to‑value.
• Leads the data scientist and machine learning engineering staff within the Center for Analytics and Insights (CAI). Mentors the team in analytics, big data, predictive modeling, prescriptive analytics, and AI/Machine Learning (ML) while instilling hypothesis‑driven experimentation, fast iteration, and product thinking from prototype to production.
• Engages with senior business unit leaders, project sponsors, and stakeholders to understand their business priorities and initiatives. Identifies and educates on where and how data science can provide the best insights and deliver measurable value tied to client outcomes and business results.
• Ensures rigorous application of controls throughout the data science project lifecycle to minimize model risks and comply with external and internal model governance requirements including documentation, observability, and post‑deployment monitoring against agreed business KPIs.
• Drives creative and innovative data science / machine learning / AI applications and results. Keeps abreast of industry, market and company trends, and partners with business leaders to champion the adoption of new data, analytic approaches, techniques and capabilities.
• Measures and quantifies the business impact of DS/ML solutions. Identifies opportunities for continuous improvement and to increase team effectiveness. Leads initiatives to achieve the improvements.
• Builds deep expertise in Vanguard's data and external data. Consults on this knowledge and applies it to complex analytic projects. Identifies data and analytic tool gaps by working with other CAI teams, business partners and IT, and recommends corrective action that unblocks value delivery.
• Elevates the stature of Analytics - helps grow the organization's appreciation for, and use of, advanced analytics.
• Works closely with Internal stakeholders including the Executive Team, Business Unit Leaders, Head of Research, IT leadership and other CAI colleagues.
• Build relationships with external stakeholders such as leading universities, third-party data providers and Data Analytics thought leaders.

• 10+ years of work experience in advanced analytics functions rooted in data science; financial services industry experience a plus.
• Proficiency in data wrangling; programming skills (Python, R); and experience with cloud‑based computing platforms.
• Deep experience in applied math, statistical techniques, machine learning methods, and AI applications.
• Experience with NLP methods, deep learning, and transformer‑based models; familiarity with generative AI.
• Excellent verbal and written communication skills to articulate complex data science concepts to non‑technical stakeholders.
• Strong project/program management skills; able to oversee multiple projects, manage trade‑offs, and drive time‑to‑value.
• Proven leadership experience in managing and developing high‑performing teams with a track record of converting prototypes into scaled solutions that achieve measurable business outcomes.
• Experience with Continuous Integration/Continuous Deployment (CI/CD) and Software Development Life Cycle (SDLC) processes and MLOps/observability practices.
• Preferred: Experience defining and tracking value metrics, running experimentation (e.g., A/B testing, causal inference), and driving stakeholder adoption from MVP through scale.
• Undergraduate degree in Analytics, Applied Mathematics, Economics, Statistics or related analytical field of study, or equivalent combination of training and experience. Graduate degree preferred.