Senior Data Scientist
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Key skills for this role
About the Role
Mastercard is seeking a Senior Data Scientist to join the Security Solutions Data Science team, focusing on AI/ML models for identity and risk in digital transactions. The role involves researching and developing scalable data science systems for agentic commerce risk identification.
Key Skills for This Role
Responsibilities
- 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
- Contribute to technical best practices across the team
Requirements
- 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
- Strong experience applying machine learning and advanced analytics to solve real world business problems
- 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
- 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
Full Job Posting
Our Purpose
- Mastercard powers economies and empowers people in 200+ countries and territories worldwide.
- Together with our customers, we’re helping build a sustainable economy where everyone can prosper.
Title And Summary
- Senior Data Scientist
Overview
- The Security Solutions Data Science team is responsible for developing AI and ML models that support Mastercard’s Identity and risk capabilities across digital transactions.
- These models are production ready and 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.
- Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience.
- In this role, you will focus on the research and development of a new space: Identifying risks in agentic commerce.
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
- 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.
- 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
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
Pay Ranges
- Vancouver, Canada: CAD 111,000 CAD 160,000 CAD
- Toronto, Canada: CAD 111,000 CAD 160,000 CAD
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