Company Description

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.

Job Description

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 extraordinarily rich data set that spans more than 3 billion cards globally and captures 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 looking for Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to tackle meaningful business problems. You will join one of the Data Science focus areas (e.g., banks, merchants & retailers, digital products, marketing) with an opportunity for rotation within Data Science to gain broad exposure to Visa’s business.

Essential Functions

• Provide technical leadership in a team that generates business insights based on big data, identify actionable recommendations, and communicate the findings to clients
• Communicate with clients to understand the challenges they face and convince them with data
• Extract and understand data to form an opinion on how to best help our clients and derive relevant insights
• Develop custom data models and algorithms to apply to data sets
• Use predictive modeling to increase and optimize customer experiences, revenue generation, data insights, and other business outcomes
• Partner with a variety of Visa teams to provide comprehensive solutions
• Synthesize ideas/proposals in writing and engage in productive discussions with external or internal stakeholders
• Provide guidance in modern analytic techniques and business applications to unlock the value of Visa’s unique data set, in keeping with market trends, client needs and emerging techniques
• Organize and manage multiple data science projects with diverse cross-functional stakeholders

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.

Qualifications

Basic Qualifications
- 10 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 5 years of work experience with a PhD degree
- 4+ years of experience applying data science to solve problems such as new customer acquisition, attrition management and product mix models
- 2+ years of experience leading 2+ data scientists in machine learning projects
- Recent experience working with and presenting to clients, such as merchants or issuers
- Recent experience coordinating offshore relationships and Data Engineering activities
- Expertise with modern distributed systems, including both Hadoop/SQL and Apache Spark
- Expertise with one or more data analytics/programming tools such as R/Python
- Expertise in the application of predictive modeling and machine learning techniques
Preferred Qualifications
- 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work 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, Marketing Research or a related technical field
- Experience leading other data scientists in machine learning projects
- Hands-on expertise with modern distributed systems, including both Hadoop/SQL and Apache Spark
- Hands-on expertise with Python and other data analytics/programming tools such as Python
- Hands-on expertise in the application of predictive modeling and machine learning techniques

Additional Information

Visa has adopted a COVID-19 vaccination policy to safeguard the health and well-being of our employees and visitors. As a condition of employment, all employees based in the U.S. are required to be fully vaccinated for COVID-19, unless a reasonable accommodation is approved or as otherwise required by law.

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.