Role Summary

This role 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. This role also includes creating data mining architectures, applying data science methodologies, and researching emerging data science techniques to identify trends and inform business decisions

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 and Skills

• 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

Special Factors

Sponsorship

Vanguard is 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.