Title and Summary

Senior Data Scientist

Overview

The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that support Mastercard's Identity and risk capabilities across digital transactions. These models are production-ready and are designed to power key products and decisioning systems across Mastercard's payment networks.

The team also leads the research and development of scalable data science systems spanning the full model lifecycle, from data acquisition and feature engineering through experimentation, validation, deployment, and monitoring. These systems are built to operate at scale and to be repeatable, resilient, and industrialized so they can support both current business needs and the exploration of emerging problem spaces.

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. As the ecosystem evolves, new forms of commerce are introducing new types of risk that require novel approaches, creative thinking, and rigorous experimentation.

In this role, you will focus on the research and development of a new space: Identifying risks in agentic commerce. This is an emerging domain where autonomous or semi-autonomous agents can initiate or influence transactions, creating new challenges for identity, trust, accountability, and risk modeling. You will help define the problem space, explore new data signals and modeling approaches, and develop scalable intelligence capabilities that can shape how Mastercard identifies and manages risk in this next generation of commerce.

What will you do?
As a Senior Data Scientist, you will work on frontier data science problems that require strong technical depth, creativity, and the ability to operate effectively in ambiguity.

Key responsibilities include:
• Execute the research and development of machine learning and analytical approaches to identify agents and risks in agentic commerce
• Explore new data signals, behavioral patterns, and entity relationships relevant to agent-driven transaction ecosystems
• Help define problem formulations in a new domain where labels, patterns, and risk taxonomies may still be evolving
• Prototype and develop machine learning solutions using Databricks, Spark, and scalable cloud-based environments
• Drive feature engineering and experimentation across structured and potentially unstructured data sources
• Identify appropriate modeling techniques based on business context, data constraints, and problem structure
• Define and implement rigorous validation frameworks to ensure solutions are reliable, generalizable, and aligned with business objectives
• Collaborate with Product, Engineering, and other Data Science partners in an Agile environment to deliver iterative progress in a rapidly developing area
• Contribute to technical best practices across the team

All About You:
Essential Skills to be successful:
• Bachelor's degree (Master's or PhD preferred) in Data Science, Statistics, Mathematics, Computer Science, or another quantitative discipline
• Strong independent research skills and resourcefulness, enabling you to find solutions and innovate.
• Strong experience applying machine learning and advanced analytics to solve real-world business problems.
• Strong experience writing clean, modular, and well-documented code following Data Science best practices. Ability to collaborate effectively through code contributions, peer reviews, and shared development workflows to ensure robust, maintainable, and efficient solutions
• Strong programming skills in Python and SQL, with experience processing and analyzing large-scale datasets
• Hands-on familiarity with scalable cloud-based data science platforms such as Databricks and Microsoft Azure
• Experience with distributed data processing frameworks such as Apache Spark
• Strong background in statistical modeling, experimentation, and machine learning evaluation
• Ability to identify appropriate techniques for complex and ambiguous problems and rigorously validate solutions
• Critical thinking and a drive to produce high-quality work, ensuring that all solutions meet rigorous standards
• Demonstrated creativity and critical thinking in emerging or loosely defined problem spaces
• Understanding of Agile methodologies, with the ability to drive iterative delivery and experimentation
• Strong communication skills, including the ability to explain complex findings to technical and non-technical audiences

Nice to Have
• Experience working with weakly labeled data or limited ground truth (i.e. heuristic approach)
• Exposure to graph analytics, entity relationships, or behavioral modeling
• Familiarity with emerging domains such as agentic systems, automation, or autonomous decisioning
• Experience with model deployment

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard's security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This is a pipeline posting for future opportunities within our team.

Pay Ranges
Vancouver, Canada: $111,000 - $160,000 CAD

Toronto, Canada: $111,000 - $160,000 CAD