Data Scientist II

Mastercard; Vancouver; On-site; CAD 91,000 - 140,000; Full time

Benefits offered by this job

Discretionary annual incentive program

Job summary

Mastercard is seeking a Data Scientist II for its Security Solutions Data Science team in Canada. You will design and deploy AI/ML models to power identity and risk solutions, focusing on merchant risk during onboarding and monitoring.

You will build scalable data assets, profiling logic, and workflows to understand merchant behavior and risk signals over time. You’ll collaborate across Data Science, Product, and Engineering in an Agile setting, contributing to feature engineering and model

Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or another quantitative discipline.
• Experience applying data science and machine learning to solve real business problems.
• Solid foundation in statistics, analytics, and core machine learning concepts.
• Experience with Python and SQL; familiarity with Pandas for data manipulation and analysis.
• Experience with writing clean, modular, and well‑documented code following Data‑Science best practices; collaborates through code reviews.
• Ability to identify analytical techniques and validate solutions through evaluation.
• Knowledge of Agile methodologies and iterative delivery.
• Willingness to learn new technologies and stay current.
• Strong communication and collaboration with teammates and stakeholders.

Responsibilities

• Analyze large‑scale transaction, merchant, and related data to identify patterns and anomalies.
• Support research and development of merchant registry and profiling for onboarding and monitoring.
• Contribute to feature engineering, entity resolution, and analytic workflows for merchant insights.
• Prototype ML and analytics solutions under guidance from senior team members.
• Build and maintain scalable data and model workflows using Databricks and Spark environments.
• Validate solutions through testing, benchmarking and performance evaluation.
• Support model monitoring, benchmarking, and iterative improvements.
• Collaborate with Data Science, Product, and Engineering in an Agile environment.

Skills

Data science experience

Statistics

Python

SQL

Pandas

Clean code practices

Collaboration

Analytical techniques

Agile experience

Communication skills

Learning mindset

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field

Tools

Databricks

Spark

Python

SQL

Job description

Data Scientist II

Overview

The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard’s Identity and risk solutions across authentication and authorization use cases. These models are production‑ready and designed to support key products and capabilities that help make digital transactions safer, smarter, and more trusted.

In addition to building models, the team is responsible for the research and development of scalable end‑to‑end data science capabilities covering the full lifecycle of model creation—from data extraction and feature engineering to validation, deployment, and monitoring. These capabilities must be designed to scale and to be repeatable, resilient, and industrialized so they can support long‑term product growth and evolving business needs.

Services within Mastercard are responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. Within this space, the Identity Data Science portfolio plays an important role in advancing intelligence‑driven solutions that enable more effective risk assessment and decision‑making across the merchant lifecycle.

You will join a dynamic and innovative team working at scale with modern big data platforms and technologies. In this role, you will focus on solving merchant risk during onboarding and ongoing monitoring through the research and development of a merchant registry and profiling capability within the Identity Data Science portfolio. This includes building the foundational data assets, profiling logic, analytical workflows, and machine‑learning approaches needed to better understand merchant behaviour, relationships, and risk signals over time.

Role: You will contribute to the design and development of data science capabilities that improve merchant risk assessment across onboarding and monitoring workflows.

Key Responsibilities

• Analyze large‑scale transaction, merchant, and related entity data to identify patterns, trends, and anomalies.
• Support the research and development of a merchant registry and profiling capability to strengthen merchant risk assessment during onboarding and ongoing monitoring.
• Contribute to feature engineering, entity resolution, and analytical workflows that improve merchant‑level intelligence.
• Prototype machine learning and analytical solutions under guidance from senior team members.
• Help build and maintain scalable data and model workflows using Databricks and Spark‑based environments.
• Identify appropriate techniques for different analytical problems and help validate solutions through structured testing, benchmarking, and performance evaluation.
• Support model monitoring, benchmarking, and iterative improvement of data science solutions.
• Work closely with partners across Data Science, Product, and Engineering in an Agile environment to support iterative delivery and continuous improvement.

Essential Skills

Essential skills to be successful:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or another quantitative discipline such as Engineering, Economics, or Physics.
• Experience applying data science and machine learning to solve real business problems.
• Solid foundation in statistics, analytics, and core machine learning concepts.
• Experience with Python and SQL; familiarity with tools such as Pandas for data manipulation and analysis.
• Experience with 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.
• Ability to identify appropriate analytical techniques and validate solutions through structured evaluation.
• Critical thinking and drive to produce high‑quality work, ensuring that all solutions meet rigorous standards.
• Understanding of Agile methodologies, with the ability to contribute to iterative delivery.
• Openness to learn and apply new technologies, staying current with industry trends and advancements.
• Good communication skills, enabling effective collaboration with team members and stakeholders.
• Self‑driven with a collaborative mindset and enthusiasm for learning in a fast‑paced, innovative environment.

Compensation & Benefits

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.

Pay Ranges:

• Vancouver, Canada: $91,000 - $140,000 CAD

Equal Employment Opportunity Mandate

Mastercard is a merit‑based, inclusive, equal‑opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [e-mail] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.