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

Team Summary

The Risk and Identity Solutions (RaIS) team provides risk management services for banks, merchants, and other payment networks. Machine learning and AI models are the heart of the real-time insights used by our clients to manage risk. Created by the Visa Predictive Models (VPM) team, continual improvement and efficient deployment of these models is essential for our future success. To support our rapidly growing suite of predictive models we are looking for engineers who are passionate about managing large volumes of data, creating efficient, automated processes and standardizing ML/AI tools.

This is a great opportunity to work with a new Engineering and MLOps team to scale and structure large scale data engineering and ML/AI that drives significant revenue for Visa. As a member of the Risk and Identify Solutions modeling organization (VPM), your role will involve developing and implementing practices that will allow deployment of machine learning models in large data science projects.

You must be a hands-on expert able to navigate both data engineering and data science disciplines to build effective engineering solutions that support ML/AI models. You will partner closely with global stakeholders in RaIS Product, VPM Data Science and Visa Research to help create and prioritize our strategic roadmap.  You will then leverage your expert technical knowledge of data engineering, tools and data architecture in the design and creation of the solutions on our roadmap.

Essential functions

• Work with a team to conduct world-class research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning, as well as deliver innovative technologies and insights to Visa's strategic products and business.
• Develop AI/Machine learning models to detect credit card information attacks.
• Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product stakeholders.
• Work with product engineering to ensure implement ability of solutions.
• Deliver prototypes and production code based on need.
• Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.
• Build needed data transformations on structured and un-structured data. Build and experiment with modeling and scoring algorithms.
• Develop custom algorithms and use packaged tools based on machine learning, data mining and statistical techniques.
• Devise and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, and A/B testing of models.
• Devise and implement methods for efficiently monitoring model effectiveness and performance in production.
• Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
• Contribute to development and adoption of shared predictive analytics infrastructure.
• Position reports to the Austin, TX office and may allow for partial telecommuting.
• Should lead a team of ML engineers/Data scientists when required.

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:
• Employer with a Ph.D./MTech degree in Computer Science, Machine Learning, Statistics, Engineering or related field.
• Machine learning
• Deep learning
• Python programming
• Advanced statistics
• Spark programming
• Graph learning
• Functional data analysis

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.