Role SummaryAs a Data Scientist, you will serve as a builder and architect of a decision product that integrates causal analysis, predictive modeling, and optimization to support high-impact business decisions. You will design the analytical engine that powers this product-defining how relationships are modeled, how uncertainty is quantified, and how outputs are generated for decision-making.
This role is well suited for someone who is technically rigorous, intellectually curious, and motivated by building analytical systems that operate in real-world environments.
Key Responsibilities- Design and develop the analytical engine that underpins a decision product, including how relationships are modeled and outputs are generated
- Apply causal inference techniques across both experimental and non-experimental settings, including situations where randomized testing is not feasible, practical, or cost-effective
- Leverage predictive modeling and optimization approaches to support decision-making and scenario analysis
- Translate complex business questions into structured analytical frameworks and scalable solutions
- Build production-quality analytical components that integrate into decision systems and can be deployed in partnership with engineering teams
- Ensure model outputs are robust, interpretable, and appropriately reflect uncertainty and underlying assumptions
- Partner cross-functionally with product, engineering, and business stakeholders to align the analytical engine with user needs and decision workflows
- Continuously evaluate and improve modeling approaches to ensure accuracy, reliability, and business impact
Qualifications- Master's or PhD in a quantitative field such as statistics, economics, mathematics, data science, operations research, or a related discipline; or equivalent combination of education and relevant experience
- 5+ years experience applying advanced analytical techniques, including causal inference, predictive modeling, and/or optimization
- 5+ years experience using quasi-experimental or observational methods to evaluate business interventions in real-world settings
- Proficiency in Python, R, or similar tools, with the ability to write clean, scalable, and production-ready code
- Strong understanding of statistical modeling, inference, and data analysis
- Ability to design analytical frameworks that support decision-making under uncertainty
- Demonstrated ability to work effectively in cross-functional and ambiguous environments
Special FactorsSponsorshipVanguard is not offering visa sponsorship for this position.
How We WorkVanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
