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.
Visa cards play a crucial role in allowing our commercial solutions partners to pay and be paid. From large enterprises to small businesses, companies depend on Visa to allow their employees ease of operation in the digital payments ecosystem and to provide them with services that can help them gain valuable insights into their customers spending as well as their own spending. The Global Data Science group supports these commercial 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 a data science director to help grow our commercial solutions business and guide our data scientists in the Bangalore office.
Essential Functions
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
• 15 years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Master’s, MBA, JD, MD) or at least 3 years of work experience with a PhD degree
Preferred Qualifications
• Minimum of 12 years of analytical experience in applying solutions to business problems
• Post Graduate degree in a Quantitative field
• Hands on experience with one or more data analytics/programming tools such as SAS/Hive/R/SQL/Python
• Prior experience in payments or financial services industry preferred
• Experience in the application of predictive modeling and machine learning techniques
• Demonstrated experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders
• Demonstrated ability to innovate solutions to solve business problems
• Results oriented with strong analytical and problem-solving skills, with demonstrated intellectual and analytical rigor
• Good business acumen with strong ability to solve business problems through data driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred
• Understanding of Cards/Payments and Banking business model would be a plus
• Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels
• Detail oriented, is expected to ensure highest level of quality/rigor in reports & data analysis
• Proven skills in translating analytics output to actionable recommendations, and delivery
• Experience in presenting ideas and analysis to stakeholders
• Exhibit intellectual curiosity and strive to continually learn
• Experience with managing project teams and providing direction and thought leadership
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.