Data Analyst, Senior Specialist / Data Scientist (Decision Analytics / Modeling)

hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role.

Analyzes data, assesses trends and develops actionable insights and recommendations in support of enterprise-wide strategic business initiatives. Develops the analytics community at Vanguard by coaching others internally and participating in external events.

Role Summary

At Vanguard, we are advancing how data informs decision-making by developing deeper insight into how business actions drive client and operational outcomes. This role sits at the intersection of advanced analytics, product development, and business strategy, helping the organization move beyond describing what happened to understanding why it happened and what to do next.

As 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 Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard 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.