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.
As a Director Data Science & Machine Learning US A2A Payments & Open Banking, you will partner closely with the VP Risk and other sales and product leaders to shape the risk & ML strategy of Visa’s A2A payments and open banking products in North America. You will build a world-class data science team to execute on the strategy and bring it to life in day-to-day risk operations. The right candidate will possess strong data science and machine learning background, with demonstrated experience in building, training, implementing and optimizing advanced ML models for payments.
A successful candidate is a technical leader with the ability to engage in high bandwidth conversations with business and technology partners and be able to think broadly about Visa’s business and drive solutions that will enhance the safety and integrity of Visa’s account to account payment ecosystem. This role represents an exciting opportunity to make key contributions to a strategic offering for Visa. The candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.
To be successful in this role, you need to be a self-starter, highly organized, and deeply understand the mindset of consumers and the structure of globally organized fraudsters. You will need to be able to build a brand-new team and hire top-tier data science talent that fits within the culture. You will also need to be able to successfully handle stakeholders on all levels across the organization, in a global environment.
Responsibilities
Build, own, and manage the data science & machine learning team for Visa’s North America Account to Account payments and open banking team
Build and manage a global team of top-tier data science talent with diverse backgrounds to execute on Visa’s product strategy in the A2A payments space
Drive key initiatives and improvements together with product and engineering to meaningfully reduce the loss exposure of the business
Partner with product, technology, sales, marketing, finance and other functions to identify and execute on key risk initiatives to limit our exposure to fraud and settlement risk
Understand the broad set of Visa’s data science and machine learning capabilities and products and identify opportunities for collaboration and creating unique advantages
Align with product teams on risk requirements and support the product and engineering teams to execute on the aligned roadmap
Build strong relationships with key stakeholders internally and externally to execute with excellence and align closely with Visa’s risk team
Responsible for driving data science & machine learning requirements, process design, and innovation (such as big data, artificial intelligence, machine learning, graph databases)
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
Preferred Qualifications
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.