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 Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to solve meaningful business problems.

Essential Functions 

• Brainstorm innovative ways to use our unique data to answer business problems

• Use LLM-based systems for natural language processing, data quality evaluation, and performance evaluation

• 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

• Identify and create key metrics and dashboards to track program success

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

• Mine and analyze data from company databases to drive optimization and improvement of product, marketing techniques and business strategies for Visa and its clients

• Work collaboratively with Data Scientists, Data Engineers and other cross-functional partners to tailor analyses and solutions to the needs of the business

• Assess the efficiency 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

• Synthesize ideas/proposals in writing and engage in productive discussions with external or internal partners

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 

Basic Qualifications

• 6-8 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
• Advanced knowledge and experience of AI/ML model development and implementation
• Experienced with building AI/ML model pipelines and creating robust and scalable AI/ML solutions.
• Experience working with LLMs in a production environment
• Track record of creating robust and scalable AI/ML/Data Science solutions and products

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.