Lead Data Scientist

Mastercard Inc.; Toronto; On-site; CAD 127,000 - 203,000; Full time

Job summary

Mastercard Inc. is seeking a Lead Data Scientist to drive fraud analytics and product innovation across the global payments ecosystem. The role focuses on extracting insights from data to reduce fraud and improve security for issuers, merchants, and consumers.

You will collaborate with stakeholders, translate business requirements into modeling solutions, and deploy AI-enabled strategies while advancing the security of the MasterCard network.

Qualifications

• Proven experience delivering stakeholder-driven solutions.
• Experience writing complex queries to extract and manipulate large data sets.
• Hands-on Python and Spark for data manipulation.
• Familiarity with UNIX environments.
• Knowledge of payments, cards and/or fraud is a plus.

Responsibilities

• Extract value from existing data sources to understand, detect and prevent fraud.
• Analyze worldwide fraud data to gain actionable insights.
• Apply modeling techniques to identify and understand fraud to protect the MasterCard network.
• Build and manage fraud-related products and services that add value.

Skills

Python

Spark

UNIX

Data analysis

Stakeholder management

Education

Bachelor's degree in a quantitative discipline

Tools

SQL

Job description

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. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary Lead Data Scientist Overview

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. 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.

What will you do?

• 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.

All about you:

• 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).

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled 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.

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 posting reflects one or more current openings on our team.

Pay Ranges Toronto, Canada: $127,000 - $203,000 CAD

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.