Summary:

　　As a Machine Learning Engineer, you will work with a highly innovative and vibrant team of Data Scientists, Machine Learning Engineers, Cloud Engineers, and Data Engineers in developing the next generation AI/ML enabled financial fraud and financial crimes prevention end-to-end solutions for Vanguard. You will perform the development of machine learning integrated software algorithms and pipelines to structure, analyze, and leverage data in a production environment. This work will transform how financial fraud fighting programs are structured. You will team up with business stakeholders to prioritize innovation ideas and work with other Engineers and Data Scientists to develop and deliver breakthrough solutions.

　　Core Responsibilities

　　1. Leads complex model development and deployment pipelines. Establishes best practices and drives innovation in data preparation and consumption. Expert in end-to-end data and model pipeline deployment and automation technologies.

　　2. Integrates and optimizes existing complex data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies expert knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Expert level knowledge in SDLC and related tools and processes. Serves as a thought partner for Machine Learning Operations team.

　　3. 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.

　　4. 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 using data discovery tools.

　　5. 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.

　　6. 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.

　　7. 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.

　　8. Participates in special projects and performs other duties as assigned.

　　Qualifications

　　1. MS in Computer Science, Statistics, Machine Learning, Data Science, Electrical Engineering, or related field, with 1+ years of experience in deploying and maintaining AI/ML related projects.

　　2. Advanced programming skills particularly in languages like Python.

　　3. Proficiency with SQL and NoSQL databases.

　　4. Proficiency in using AWS machine learning services, such as Sagemaker, for model development, training, and deployment.

　　5. Proficiency in designing and implementing scalable data pipelines that support machine learning workflows.

　　6. Proficiency in AWS CloudFormation for infrastructure as code. Experience with CI/CD practices for both machine learning and data engineering workflows.

　　7. Experience with data processing technologies, such as Apache Spark, AWS Glue and Hadoop.

　　8. Proven ability to develop and deploy machine learning models with robust data architectures.

　　9. Ability to convey technical concepts to diverse stakeholders.

　　10. Strong technical skills on ML/AI concepts with proven track record is a plus.

　　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.