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Salary
≈ $91k – $181k per year (Estimated)
Location
In office (Toronto)
Seniority
Staff
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Oct 3, 2026. Mastercard scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Mastercard is a global payments technology company headquartered in Purchase, New York, operating the card network that connects consumers, merchants, banks and governments and providing data, cybersecurity, loyalty and open banking services. Founded in 1966 as the Interbank Card Association and listed on the New York Stock Exchange since 2006, it processes transactions in more than 200 countries and territories; this record is its UK domain, with major teams in London, Dublin, New York and Toronto. It hires software engineers, data scientists, AI engineering leaders, product managers, information security executives, regulatory counsel and program management interns.

Join Mastercard's Cyber and Intelligence Solutions team as a Lead Data Scientist. In this role, you will analyze worldwide fraud data, apply modeling techniques to detect and prevent fraud, and build new fraud-related products and services. You should have experience with Python, Spark, and UNIX, as well as a degree in a quantitative discipline.

Missions

  • Contribuer à l'innovation, au développement et à la gestion des produits et services de Mastercard pour répondre aux besoins en matière de risque et de sécurité.
  • Utiliser votre expertise en science des données pour analyser les données sur la fraude à l'échelle mondiale et appliquer des techniques de modélisation pour identifier et comprendre la fraude.
  • Construire et gérer de nouveaux produits et services liés à la fraude qui apporteront de la valeur à nos clients et augmenteront les revenus.

Profil recherché

- Familiarity and experience with UNIX highly desired

- Experience with Python and Spark for data manipulation is required

- Excellent inter-personal skills, able to work with colleagues remotely as well as in -person

- Experience writing complex queries to efficiently extract and manipulate large amounts of data

- Record of accomplishment in learning and applying new techniques and data analysis languages

- 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

- Degree in quantitative discipline preferred (e.g., Mathematics, Statistics, Physics, Computer Science, Decision Science or Engineering)

- Proven experience working with stakeholders to deliver state-of-the-art solutions that adhere to their requirements

- Ability to combine knowledge across multiple disciplines to solve problems

- Subject matter expertise in payments, cards, and /or fraud or proven ability to learn and master new subject matter areas

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