Optimization Research Scientist

About the Role

You will be part of a high-profile Applied R&D team focused on building creative and impactful solutions in investment management and finance. This multinational research lab supports the research, development, and deployment of advanced optimization, machine learning, and quantitative methods—including deep learning, convex optimization, and stochastic simulation—across several parts of the investment management process. This opportunity is best suited for individuals with strong applied research experience who are excited to work at the intersection of quantitative modeling, mathematical modeling, machine learning, and investment decision-making. We are specifically looking for individuals with hands-on deep learning experience, strong quantitative intuition, and the ability to contribute rigorous, systematic solutions in collaboration with research, engineering, and investment partners.

Responsibilities

• Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling.
• Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making.
• Mentors and develops junior data scientists and analysts.
• Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps.
• Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses.
• Brings structure to requests and translates requirements into an analytic approach.
• Guides test design, research design, and model validation.
• Provides statistical consultation services.
• Serves as the analytics expert on cross-functional teams for large strategic initiatives and contributes to the growth of the analytic community.
• Prepares and delivers insight presentations and action recommendations.
• Communicates complex analytical findings and implications to business leaders.
• Participates in special projects and performs other duties as assigned.

Qualifications

• Experience in applied research or quantitative modeling, with an ability to independently execute well-scoped research efforts and contribute to larger multi-disciplinary projects.
• Strong experience building machine learning or deep learning models to address specific problem statements.
• Experience or strong familiarity with quantitative trading concepts and systematic workflows.
• Proficiency in Python and comfort working in development environments such as SageMaker, Databricks, or similar platforms.
• Experience designing and interpreting evaluation frameworks using out-of-sample testing, simulation, and backtesting.
• Experience with fixed income investment management problems is preferred.
• Participation or completion of the CFA or related financial knowledge is valuable.
• Ability to read and reproduce research papers in computational settings.
• Participation in systematic or quantitative workflows in Investment Management is a plus.

Academic Background

• Undergraduate degree in a related STEM field with strong modeling and programming foundations required.
• Graduate degree, or equivalent industry experience in applied research, machine learning, quantitative modeling, or engineering workflows, is preferred.
• Strong coursework in mathematics, statistics, optimization, machine learning, or related analytical disciplines is valuable.

Strong written and oral communication skills.

Special Factors

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.