OverviewServices within Mastercard are responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. The Data Science team develops advanced AI and machine learning solutions that power critical products across Mastercard's network. This role supports the merchant/acquiring side, working with large‐scale transaction data and models focused on merchant risk, payments fraud detection, merchant credit risk, and Anti‐Money Laundering.We are seeking a Lead Data Scientist to drive the design, delivery, and success of data science initiatives. The position combines deep technical expertise with end‐to‐end project ownership, strong production focus, and cross‐functional leadership to deliver high‐impact, production‐ready machine learning solutions. This full‐time hybrid role is based in Toronto, Canada, with an expectation of at least three days per week in the office.RoleDesign, build, evaluate, enhance, and monitor machine learning and statistical models focused on merchant risk, fraud detection, merchant credit risk, Anti‐Money Laundering, and payment‐related risk use cases.Oversee feature engineering, model training, validation, packaging, production support, and performance monitoring across the full model lifecycle.Ensure high standards for model quality, robustness, interpretability, documentation, and production reliability.Lead hands‐on model development, experimentation, and technical problem solving using large‐scale merchant/acquiring and transaction data.Partner with product, engineering, development, QA, customer success, and business stakeholders to define problem statements, success metrics, implementation needs,



and release readiness.Collaborate closely with AI/ML engineering and development teams to support production model deployment, scaling, operationalization, and ongoing implementation activities.Operate independently in a lean, highly collaborative team, driving initiatives end‐to‐end with limited oversight while balancing speed, quality, and production impact.Deliver work through typical project cycles of approximately 4–6 weeks from development through delivery.Communicate insights, recommendations, technical trade‐offs, and model performance clearly to both technical and non‐technical audiences.All About YouBachelor's or accelerated Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.Relevant experience in data science, AI, or machine learning roles, with proven ability to own and deliver data science projects end‐to‐end.Strong Python expertise with experience in machine learning model development, standard data science libraries, and distributed data processing frameworks such as PySpark.Hands‐on experience with Databricks or similar distributed data platforms, with the ability to work with large‐scale, complex transaction datasets.Experience with machine learning techniques and tools relevant to fraud and risk modeling, including XGBoost or similar approaches.Proven ability to design, build, deploy, monitor, maintain, and improve production‐ready machine learning models.Experience working with transactional,



merchant, acquiring, or behavioral data at scale, with strong problem‐solving and critical‐thinking skills.Effective communicator with the ability to influence stakeholders and explain complex technical concepts to technical and non‐technical audiences.Ability to balance hands‐on technical work with leadership responsibilities in a lean, cooperative environment.PreferredAdvanced degree in a relevant quantitative field.Experience in payments, acquiring, transaction processing, merchant risk, AML, fraud, or financial crime analytics.Familiarity with fraud detection, merchant credit risk, anomaly detection, behavioral modeling, graph techniques, model explainability, governance frameworks, or regulatory requirements in financial crime.Corporate Security ResponsibilityAll activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organization. Employees are expected to: abide by security policies and practices; ensure confidentiality and integrity of accessed information; report any suspected violations or breaches; and complete mandatory security trainings in accordance with Mastercard's guidelines.Pay RangesVancouver, Canada: $127,000 – $203,000 CADMastercard 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. In the US or Canada, if you require accommodations or assistance to complete the application or recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. #J-18808-Ljbffr

📌 Lead Data Scientist (Vancouver)
🏢 Mastercard
📍 Vancouver