Title And SummarySenior AI EngineerOverviewThe Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (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—from data acquisition and feature engineering, through experimentation and validation, to deployment and monitoring. These systems are built to operate at scale and are designed to be repeatable, resilient, and industrialized, supporting both current business needs and the exploration of emerging problem spaces.Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. Within this mission, the Identity Data Science portfolio plays a significant role in developing intelligence‑driven solutions that improve how risk is understood and managed across the merchant lifecycle, including building a unified merchant view and trust profile.You will join a agile and innovative team working at petabyte scale with cutting‑edge big data platforms and technologies such as Databricks and Apache Spark. Our mission is to streamline and automate the repetitive aspects of data science to accelerate innovation in AI/ML‑driven fraud detection. We specialize in building scalable pipelines, robust feature engineering workflows, and shared tooling that enables faster and more reliable model development and deployment.RoleAs a Senior AI Engineer, you will:Be an integral part of a creative and innovative team, contributing to collaborative projects and sharing insights to drive engineering and data science excellenceWork with cutting‑edge big data platforms (e.G., Databricks, Apache Spark) at petabyte scale, pushing the boundaries of data processing and model enablementPartner closely with Data Science teams to enable seamless R&D;, scale models, features, and experimentations into reliable systemsSupport the deployment of model features and model artifacts, ensuring seamless integration into production environments and downstream decisioning systemsWrite clean, testable, and maintainable code, ensuring solutions are robust, efficient, and production‑gradeDesign, build,



and maintain data pipelines that integrate multiple data sources to support a unified merchant registry and trust profile, enabling richer datasets and unlocking new opportunities for innovationCollaborate with data operations and governance teams to move and manage data in compliance with security standards, policies, and regulatory requirementsContribute to the design and evolution of scalable, entity‑centric data models that support merchant identity resolution and longitudinal profilingAutomate and maintain data workflows in distributed environments, improving reliability and operational efficiencyAnalyze and optimize ETL/ELT processes to support high‑performance data access and model executionImplement testing frameworks and monitoring capabilities to ensure production solutions are reliable, observable, and continuously improvingSupport incident response, debugging, and performance tuning of production AI/ML systemsAbout YouEssential skills to be successful:Proven track record of self‑directed learning, demonstrating the ability to acquire new skills and knowledge independentlyStrong independent research skills and resourcefulness, enabling you to find solutions and innovate in data engineeringStrong understanding of data pipelines and end‑to‑end ML model development workflows, with exposure to entity‑centric data systemsExperience with Python and SQL, showcasing the ability to write clean, readable, and maintainable codeExperience with big data technologies (e.G., Spark, distributed compute frameworks)Hands‑on experience with cloud platforms such as Databricks, AWS, or GCPCritical thinking and a drive to produce high‑quality work, ensuring all solutions meet rigorous standardsStrong communication skills, enabling effective collaboration with team members and stakeholdersExperience collaborating across data science, engineering, and governance teamsAbility and interest in problem‑solving, with a proactive approach to tackling challengesOpenness to learn and apply new technologies, staying current with industry trends and advancementsFamiliarity with Agile methodologies, with the ability to drive iterative delivery and cross‑team collaborationBachelor’s degree in Computer Science, Data Analytics, Mathematics, Software Engineering,



or a related field or equivalent practical experienceContributions to platform standardization, reusability, and shared tooling across teamsNice to HaveExperience working in hybrid environments (cloud and on‑premises)Familiarity with ML lifecycle and CI/CD practices for data and ML workflowsExperience with data governance, lineage, and metadata managementExposure to batch, streaming, or real‑time data pipelines and production ML monitoring/observabilityExperience supporting high‑scale production systems in merchant, fraud, or payment domainsUnderstanding of security, compliance, and handling sensitive dataExperience designing scalable databases and data models such as business registriesExperience with database updates and maintenanceMastercard 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 [email protected] 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 ResponsibilityAll activities involving access to Mastercard assets, information, and networks come 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, andComplete 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 is a pipeline posting for future opportunities within our team.Pay RangesVancouver, Canada: $111,000 - $160,000 CADToronto, Canada: $111,000 - $160,000 CAD#J-18808-Ljbffr

📌 Senior Data Engineer - C$111,000 - C$160,000 A Year (Winnipeg)
🏢 Mastercard
📍 Winnipeg