Lead, Data Analytics & Modeling

In partnership with the Financial Advisor Services (FAS) organization, Vanguard's Chief Data & Analytics Office is driving a critical transformation in how data and analytics power FAS's vision of being the Advisor to the Advisor. This role sits at the center of that transformation.

The Manager, Data Analytics & Modeling is a hands-on technical leader responsible for designing, building, and scaling high-quality data solutions that enable better decision-making across the FAS business. While this role carries a Manager title, it is intentionally highly technical and execution-oriented. The ideal candidate is a strong individual contributor who actively writes code, designs data models, and partners closely with engineering teams to deliver scalable, production-ready data assets.

This role blends deep technical expertise in data modeling, analytics, and data engineering with the ability to lead and mentor a small team of analysts.

Core Responsibilities:

Hands-On Technical Leadership

• Design, build, and maintain scalable data models, datasets, and analytical solutions, with a strong focus on correctness, performance, and reusability.
• Write, review, and own production-quality SQL and Python code used in data pipelines, transformations, and analytical workflows.
• Partner closely with data engineering and platform teams to influence data architecture, modeling standards, and tooling choices.
• Ensure analytics solutions are built on well-architected, trusted, and well-governed data foundations.

• Lead the development of high-impact dashboards, metrics, and analytical products that support strategic and operational decision-making.
• Translate complex business problems into clear analytical approaches, data models, and technical solutions.
• Apply advanced analytical techniques (e.g., predictive analytics, statistical modeling, machine learning where appropriate) to identify trends, risks, and opportunities.
• Drive automation and standardization of reporting and analytics workflows to reduce manual effort and improve scalability.

• Hire, mentor, and develop a team of analysts, setting a strong technical bar and fostering hands-on skill growth.
• Provide technical guidance through code reviews, design discussions, and modeling best practices.
• Work directly with business stakeholders to align analytics solutions to business outcomes, while maintaining strong technical rigor.
• Contribute to analytics roadmaps and prioritization, balancing near-term delivery with long-term architectural health.

• 8+ years of experience in data analytics, data engineering, or related technical roles, with demonstrated hands-on delivery.
• Strong experience designing data models (e.g., dimensional, semantic, or analytical models) that support scalable analytics.
• Advanced proficiency in SQL and Python; comfort owning and maintaining complex analytical codebases.
• Experience working closely with data engineering teams on data pipelines, architecture, and platform design.
• Deep understanding of analytics and BI concepts, with experience using tools such as Power BI, Tableau, Looker, or similar.
• Proven ability to translate ambiguous business problems into well-designed technical solutions.
• Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.

• Experience leading or mentoring analysts in a player-coach capacity.
• Familiarity with modern data platforms (cloud data warehouses, transformation frameworks, orchestration tools).
• Experience delivering analytics in regulated or complex enterprise environments.
• Background in financial services, wealth management, or advisor-focused businesses.