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.
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 outstandingly rich data set that spans more than 3 billion cards globally and collects 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 hiring Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to solve meaningful business problems. You will join one of the Data Science focus areas (e.g., banks, merchants & retailers, digital products, and marketing) with a rotational opportunity within Data Science to gain broad exposure to Visa’s business.
Essential Functions
Prioritize and lead multiple data science projects with diverse multi-functional partners
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
• 4 years of work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Master’s, MBA, JD, MD) or 0 years of work experience with a PhD degree
Preferred Qualifications
• 6-8 years of work experience with a Bachelor’s Degree or 4-6 years of work experience with an
• Advanced Degree (e.g. Master’s, MBA, JD, MD) or 3 years of experience with a PhD
• 4+ years’ experience in data-based decision-making or quantitative analysis
• Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field
• Extracting and aggregating data from large data sets using SQL/Hive or Spark
• Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark
• Generating and visualizing data-based insights in software such as Tableau
• Communicating evidence based insights and conveying relevant recommendations
• Leading and coordinating work in Office software
• Building predictive and descriptive statistical models using machine learning tool kit, Jupyter notebooks, Python, and/or SAS
• Data mining and statistical modeling (e.g., regression modeling, clustering techniques, decision trees, etc.)
• Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required
• Running projects from scoping to delivery, and engaging with internal/external partners
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.