As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.

At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.

You're an Individual. We're the team for you. Together, let's transform the way the world pays.

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 looking for Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to seek important 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. 

The position is based at Foster City, CA or our other offices in the U.S. 

Essential Functions 

• Create automated data ingestion pipeline with Spark, Python or other tools and provide scalable data engineering solution for Visa Consulting and Analytics 

• Understand credit card portfolio profitability and develop financial allocation and forecasting models, e.g. calculate NPV, net profit margin using P&L data 

• Ensure issuer data accuracy, integrity and consistency. Develop self-service reporting tools with financial critical metrics and facilitate issuer consulting engagements including data exchange 

• Assist in analytics and communication of key financial revenue driver trends and performance 

• Drive in-depth analysis to help issuers increase cardholder usage and engagement, providing data driven insights and meaningful recommendations to improve cardholder activation and usage 

• 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 

• Be an out-of-the-box problem solver who is passionate about brainstorming innovative ways to use our outstanding data to answer business problems 

• Connect 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 visualizations to make your sophisticated analyses accessible to a broad audience 

• Find opportunities to craft products out of analyses that are suitable for multiple clients 

• Assess the effectiveness and accuracy of new data sources and data gathering techniques 

Basic Qualifications 

• 2 years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD) 

Preferred Qualifications 

• 2+ 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 

• Presenting data-driven insights and conveying meaningful recommendations 

• Leading and coordinating work in Office software such as Word, Excel, PowerPoint and/or Teams 

• 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 

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.