Supports and performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment.
Core Responsibilities
Leverages data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySprak, GlueETL).
Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.
Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
Supports data discovery & automated ingestion for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.
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. Participates in and influences ongoing business planning and departmental prioritization activities.
Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.
Participates in special projects and performs other duties as assigned.
Qualifications
Undergraduate degree or equivalent experience; a graduate degree is preferred.
Minimum of 5 years of relevant work experience.
At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
Experience with API design and development is a plus.
Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
Understanding of solution architecture for building end-to-end machine learning data pipelines.
Special Factors
Sponsorship
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.
Skills Required
- 5 years of relevant work experience
- 3 years of hands-on experience designing ETL pipelines using AWS services
- Proficiency in Python
- Understanding of cloud technologies and NoSQL databases
- Familiarity with machine learning libraries and frameworks
Vanguard Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Vanguard and has not been reviewed or approved by Vanguard.
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Retirement Support — Retirement support appears unusually strong through a 401(k) design that includes a match plus an additional employer contribution, which can materially lift long-term total rewards. HSA seeding and an enhanced employer match further strengthen the savings-and-benefits value of the package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle support is reinforced by a sizable annual FlexFund stipend that can be applied across many day-to-day categories such as fitness, childcare, and other personal expenses. On-site or virtual clinics and fitness options add practical health and wellness convenience.
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Affordable Benefits — Healthcare and related benefits are positioned as comparatively affordable via heavily subsidized medical plans and broad coverage options. This affordability can offset moderate base pay for employees who place higher value on out-of-pocket cost reductions.
Vanguard Insights
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. For Commenting Guidelines & Important information, visit here: http://vanguard.com/linkedin Vanguard Marketing Corporation, Distributor.
