Responsibilities: 

• Leads and personally drives a focused portfolio of high-priority applied AI and machine learning initiatives across Investments and Finance, working hands-on to translate consequential business and investment problems into scientifically rigorous, scalable AI capabilities that drive business value through elevation to production systems. 
• Sets scientific direction in conjunction with senior leadership and personally develops and evaluates research hypotheses, model approaches, and experiments, challenging methodological assumptions and empirical evidence from problem formulation through validation and production transition. 
• Leads and develops a small, multidisciplinary team of researchers and engineers as a player-coach, providing technical direction, working alongside the team on complex research problems, and setting clear standards for research quality and professional development. 
• Elevate and evolve established standards for research quality, reproducibility, explainability, documentation, and model governance. 
• Hires, evaluates, and supervises employees. Provides guidance and training as necessary to develop crew. Sets performance standards, reviews performance, and makes informed compensation decisions in accordance with all applicable Human Resources policies and procedures. 
• Partners with senior stakeholders to frame consequential business and investment challenges as tractable applied research questions and build out project proposals to secure alignment and resourcing. 
• Present research and technical findings, recommendations, and business implications to both internal and external senior business leaders. 
• Contribute and be a leader within the lab in its collaborative culture of learning. 
• Evaluate existing research hypotheses, alternative model approaches, methodological assumptions, and empirical evidence. 
• Guide research from problem formulation through experimentation, validation, and production transition. 
• Connect business strategy, applied research, governance, and production engineering across the AI development lifecycle. 

Education & Experience:  

• Minimum 8 years related work experience in analytical roles and research roles.
• Bachelor’s degree (B.E./B.Tech) in Applied Mathematics, Analytics, Statistics, Economics, or Computer Science; Master’s degree or PhD preferred.
• Minimum of 2+ years of people leadership experience managing researchers, data scientists, or professionals in similar analytical roles, including responsibility for performance management, coaching, and employee development.
• Programming skills to access, transform, and prepare large-scale data for statistical modeling.
• Experience utilizing statistical and machine learning methods, especially deep learning.
• Experience personally developing and leading applied AI, machine learning, quantitative research, or systematic investing initiatives.
• Experience providing technical direction to multidisciplinary teams of researchers, scientists, and engineers.
• Experience with investment management practices, financial data, quantitative methods, and research workflows.
• Experience with machine learning, statistical modeling, experimental design, back testing, and model validation.
• Experience evaluating research hypotheses, alternative model approaches, methodological assumptions, and empirical evidence.
• Experience guiding research from problem formulation through experimentation, validation, and production transition.
• Experience establishing standards for research quality, reproducibility, explainability, documentation, and model governance.
• Experience presenting technical findings, model limitations, and strategic recommendations to senior business stakeholders.

Preferred Qualifications: 

• Master’s degree, PhD, or equivalent research experience in machine learning, data science, applied mathematics, or a related discipline. 
• Experience in investment management or quantitative finance. 
• Experience with AI governance and production machine learning practices. 
• Experience developing and validating machine learning solutions for complex problems. 
• Experience establishing reusable research standards, explainability practices, or enterprise AI capabilities. 

Special Factors

Sponsorship

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.