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 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 across regions. 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.

Why this is important to Visa

Cross-border payments are becoming increasingly important to consumers, businesses, banks, and Visa. Technology is eliminating borders and reducing friction. Shopping is becoming a global process. Travel and tourism are an important source of economic growth in many markets of the world. Against this backdrop, Visa must rally our resources and capabilities to ensure we are capitalizing on the opportunities in this important, fast-moving, and competitive segment of our business.

To meet this challenge, we have a global Cross-Border business unit to drive and manage our activities across regions and products. The Cross-Border business unit provides a strategic focus for our global efforts, while ensuring regional teams are established and capabilities are deployed for local execution.

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
• Brainstorm innovative ways to use our unique data to answer business problems
• 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 visualizations to make your complex analyses accessible to a broad audience
• Find opportunities to craft products out of analyses that are suitable for multiple clients
• Work with stakeholders throughout the organization to identify opportunities for leveraging Visa data to drive business solutions
• Mine and analyze data from company databases to drive optimization and improvement of product, marketing techniques and business strategies for Visa and its clients
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• 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              

• 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
• 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
• 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.)
• 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 data-driven insights and conveying actionable recommendations
• Managing and organizing work in Office software such as Word, Excel, PowerPoint and/or Teams
• Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required
• Managing analytics/data science projects from scoping to delivery, and engaging with internal/external stakeholders