Senior Data Engineer – MLOps

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners and internal business units. The Global Data Science group supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally and captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and various groups at Visa. To support our rapidly growing group we are looking for data engineers who are equally passionate about the opportunity to use Visa’s rich data to tackle meaningful business problems.

This position will be part of VCA (Visa Consulting & Analytics) function in building and maintaining global data assets and engineering solutions. In this role, you will be responsible for helping to develop a global engineering and solutions team focused in standardized development of Consulting Solutions. You will partner closely with Global stake holders in Visa consulting, data Science and data engineering teams. You will get chance to leverage your strategic planning, business analysis and technical knowledge of data engineering, tools and data architecture solutions. In addition to managing our portfolio of data engineering assets and solutions globally, you will play key roles in building relationships with Consulting partners to develop effective market response strategies. You will also be a hands-on expert able to direct & navigate both data engineering and data science teams to build effective data engineering solutions. The ideal candidate will have a mix background with data engineering, data science, and machine learning engineer.

Essential Functions

• Build MLOps pipelines to support model development, model production, model validation, model performance monitoring, model recalibration, continuous integration, continuous delivery of AI/ML models.
• New model development and existing model re-training, performance evaluation and score optimization. Preferable to have data science knowledge and experience in designing, developing and implementing Deep Learning methodologies, and newer ML model implementations at scale.
• Build and maintain high performing ETL processes including data quality and testing aligned across technology, internal reporting and other functional teams.
• Build ETL pipelines in Spark, Python, HIVE or Scala that process transaction and account level data and standardize data fields across various data sources
• Exposure to model management and governance practices. Ability to take decisions around model drift to monitor and refine models continuously.
• Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs like performance dashboards, predictive models scoring for client’s deliverables
• Define and build technical/data documentation and experience with code version control systems (for e.g., git). Ensure data accuracy, integrity and consistency
• Strong understanding of development and implementation aspects of ML/AI, especially on billion-scale datasets. Ability to take small scale developed models as input and implement with requisite configuration and customization, while maintaining model performance
• Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic Qualifications

• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualificat