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.
Top Skills
What We Do
We are a community of 30 million who think – and feel – differently about investing. Together, we’re changing the way the world invests.
Since our founding in 1975, helping our investors achieve their goals is our sole reason for existence. With no other parties to answer to and therefore no conflicting loyalties, we make every decision—like keeping investing costs as low as possible—with only your needs in mind.
Vanguard is one of the world's largest investment companies, offering a large selection of high-quality low-cost mutual funds, ETFs, advice, and related services. Individual and institutional investors, financial professionals, and plan sponsors can benefit from the size, stability, and experience Vanguard offers. As of April 30, 2019, we managed more than $5.6 trillion in global assets. In addition, we have 189 funds in the United States and 225 funds in global markets.
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