Machine Learning Scientist (1-2 years'' experience)

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.

The ML Scientist will work with a world-class team at the middle of a global payments revolution focusing on multiple convergent trends across all geographies that Visa operates in. You will conduct extremely high-quality applied AI & ML research and contribute to the long-term research agenda in large-scale machine learning for Visa. This role will make key contributions to Visa's strategic vision as a world-leading data-driven company. You will deeply understand the business problem, formulate it as a mathematical problem, identify datasets from which alpha can be derived, and finally provide innovative solutions for Visa's strategic products and business. The successful candidate must have strong academic track record, deep understanding of algorithms, hands-on experience on very large sized datasets, and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, excellent collaboration skills, and a commitment to pushing the boundaries of applied sciences.

Essential Functions

• Formulate business problems as technical and mathematical problems, and collaborate with business and product stakeholders to ensure key business drivers are impacted.
• Work with product engineering to ensure implementability 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 end-to-end ML pipelines across data extraction, feature engineering, training, inference, and validation, using very large structured and unstructured data sources. This includes development of custom algorithms as well as use of packaged tools for machine learning, analytics, and statistical techniques.
• Devise and implement methods for adaptive learning with controls on efficiency, methods for explaining model decisions where vital, model validation, A/B testing of models.
• Devise and implement methods for efficiently monitoring model efficiency and performance in production.
• Contribute to development and adoption of shared predictive analytics infrastructure.
• Use AI copilots to automate and gain efficiency across the complete ML model development lifecycle.

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.

Basic Qualifications
• ML scientist: 2 or more years of relevant experience with an Advanced Degree (e.g. Masters), Trained and/or deep experience in mathematical concepts underlying statistics, machine-learning, algorithms, and data structures.


• Relevant coursework in machine learning, deep learning, and modeling techniques using TensorFlow. Ability to read and critique SOTA implementations in research papers.
• Intermediate to Expert programming skills in at least one of Python, Scala.
• Experience working with large datasets using tools like PySpark. Experience in Ray or Dask is a plus.
• Experience in building and deploying models as micro-services.
• Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.

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.