Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Visa has the world's largest consumer payment transaction data set. We see data on over 100 billion transactions per year from all over the world. Visa Predictive Models (VPM) team develops and maintains predictive machine learning models to primarily support Visa Global Data Products, Security and Identity Products, and Cardinal Commerce. Using mostly VisaNet data and leveraging Machine Learning (ML) and Artificial Intelligence (AI), our model scores help Visa clients all over the world for fraud defense, identity verification, smart marketing, credit underwriting and etc. Through our models and services, VPM fuels the growth of Visa clients, generates and diversifies revenues for VISA, greatly improving Visa Card customer experience and their financial lives. To support our rapidly growing group we are looking for Data Scientists who are equally passionate about the opportunity to use Visa's rich data to tackle meaningful business problems.

Responsibilities

• Identify and test opportunities and offer recommendations to improve Credit Risk products.
• Build and validate cutting-edge predictive models with advanced machine learning techniques such as Gradient Boosting, Deep Neural Networks (e.g., RNN) to predict consumer and business credit risk
• Use Big Data technologies to analyze large and complex datasets to solve a wide array of challenging business problems
• Adopt best practices to write and test complex predictive model software packages for model production deployment
• Work with a cross functional team including Product Managers, Data Engineers, and Platform Engineers to deploy model in production
• Provide model operation support, including model monitoring, score calibration, etc.
• Conduct research in latest and emerging modeling technologies and adopt in production models
• Conduct and present model ad-hoc analysis to internal and external clients
• Manage model risks in line with Model Risk Management requirements.

Besides the primary location of Arlington, VA, an ideal candidate can also be in Atlanta, GA , Foster City, CA, and Miami, FL.

Flex Work Arrangement - Hybrid Position - 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 two days a week, Tuesdays and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

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.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.