Lead Data Scientist

Who you are

• Proven experience working with stakeholders to deliver state-of-the-art solutions that adhere to their requirements
• Record of accomplishment in learning and applying new techniques and data analysis languages
• Experience writing complex queries to efficiently extract and manipulate large amounts of data
• Experience with Python and Spark for data manipulation is required
• Hands-on experience designing, building, or deploying agentic AI systems, such as LLM-based agents that plan, use tools, and execute multi-step tasks autonomously, is strongly preferred
• Experience preparing presentations for management/clients that present insights clearly and efficiently
• Familiarity and experience with UNIX highly desired
• Subject matter expertise in payments, cards, and /or fraud or proven ability to learn and master new subject matter areas
• Ability to combine knowledge across multiple disciplines to solve problems
• Excellent inter-personal skills, able to work with colleagues remotely as well as in –person
• Degree in quantitative discipline preferred (e.g., Mathematics, Statistics, Physics, Computer Science, Decision Science or Engineering)

What the job involves

• The Cyber and Intelligence Solutions team is responsible for innovation, development and management of our products and services to address evolving risk and security needs for all of Mastercard’s customers across the world including Banks, Merchants, Fintechs and of course consumers
• The Lead Data Scientist will be a key contributor in helping Mastercard develop and deliver actionable insights and products to help issuers, acquirers and merchants reduce fraud
• You will be a key player in helping Mastercard extract value from existing data sources in order to better understand, detect and prevent fraud
• Use your data science expertise and skills to analyze worldwide fraud data to gain insights regarding fraud
• Apply modeling techniques to identify and understand fraud to protect the MasterCard payment network
• Build and manage new fraud related products and services that will provide value to our customers and increase revenue