Vanguard is one of the world's largest and most respected investment management companies, known for its client-centric approach, low-cost investment products, and commitment to long-term, data-driven investment strategies. Our Center for Analytics and Insights (CAI) team is actively working on advancing AI innovation and building AI driven products for our business lines. The team aims to ultimately accelerate critical business solutions with AI capabilities. This role will directly support the Intelligent Outreach program to build AI capabilities that improve sales and distribution, client targeting, and opportunity assessments as part of touchpoint and distribution strategy.  If you are a strategic problem solver with a passion for innovation and a proven track record in building analytics strategies and delivering complex initiatives in a cross-functional environment, we invite you to apply for this exciting opportunity.
Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of machine learning models and their deployment architecture.

Responsibilities:

• Develops complex data pipelines and implements data engineering design principles for iterative data pipeline development to drive scale and efficiency. Proficient in model development environments and coding best practices to enable model deployment.
• Integrates and optimizes existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Proficient in SDLC processes and related tools and technologies.
• Partners with data science teams to review model ready dataset document/feature documentation. Develops data model design and document and reviews for completeness with data science teams.
• Partners with data science teams to understand data requirements, performs data discovery for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives efficiency through the use of data discovery tools.
• Engages with internal stakeholders to understand and probe business processes and develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
• Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.
• Serves as a machine learning engineering subject matter expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.
• Participates in special projects and performs other duties as assigned.
• Designs and implements statistical analysis frameworks and protocols to uncover business trends across functions like marketing, supply chain, and economics.
• Applies advanced data mining techniques to build scalable models for deriving actionable insights from large-scale data sets.
• Explores and integrates evolving methodologies in machine learning and big data science to enhance decision-making strategies.

Qualifications:

• Minimum 8 years of experience in machine learning engineering or data science roles
• Bachelor’s degree (B.E./B.Tech) in Computer Science, Data Engineering, AI/ML, or related fields, or a Master’s degree/Diploma in Computer Science or Data Science
• Strong expertise in data pipeline development, statistical modeling, SDLC, AI/ML concepts, model monitoring, and stakeholder engagement across domains

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.