Title and Summary

Senior Specialist, Product Management

Overview
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.

The Identity organization develops data-driven platforms and products that enable authentication, fraud detection, and identity intelligence across Mastercard's global network. This role supports the engineering and product teams to build foundational capabilities that power these solutions.

This role supports product development by enabling rapid, data-driven decision-making through analysis, experimentation, and data exploration. The position focuses on answering critical product questions, evaluating product opportunities, and quantifying value to ensure teams are building the highest-impact capabilities.

Role
The Senior Specialist, Product Development is an embedded, product-oriented data specialist supporting Identity product teams. This individual partners closely with Product Managers to design analyses and experiments that test product hypotheses and inform engineering and product decisions.

The role is responsible for analyzing complex, interconnected datasets, developing structured experiments, and generating insights that guide product direction, particularly in areas such as fraud outcomes, data enrichment value, and cost optimization.

Initially focused on analyzing existing data, the role will ultimately include building datasets, developing pipelines, and creating repeatable reporting processes to support ongoing product evaluation. The individual will work across multiple concurrent analyses, support ongoing initiatives, and contribute recommendations that influence product strategy.

This role operates within a collaborative product environment, with guidance from Director- and Manager-level Product Managers, and requires strong technical depth, curiosity, and the ability to clearly communicate complex findings to diverse audiences.

All About You
Previous experience as a data scientist, engineer, or data analyst
Strong proficiency in PySpark / Spark Scala and distributed data processing
Experience with AWS infrastructure and data platforms (S3, EC2, or similar)
Advanced experience with SQL and Python for data analysis
Experience using Databricks and notebook-based workflows
Familiarity with data visualization tools such as Tableau or Microsoft BI
Solid understanding of statistics and experiment design
Ability to analyze large, complex, and interdependent datasets and understand system-level relationships
Experience designing analyses or experiments to support product/business decision-making
Ability to generate clear, actionable recommendations based on data insights
Strong technical foundation and ability to independently write and validate code; candidates must demonstrate depth of understanding in their analyses
Strong communication skills, with the ability to translate technical results into business recommendations to mixed technical and non-technical audiences
Ability to manage multiple concurrent projects and deliver on deadlines
Self-starter with strong curiosity, initiative, and willingness to ask questions
Experience establishing new, replicable, and organized processes in data pipelines and analyses
Experience working in product-driven environments, partnering with Product Managers and Engineering teams
Ability to support product teams by translating business questions into structured analyses and testable hypotheses
Experience contributing to cost optimization, value quantification, or performance analysis initiatives
Ability to use AI tools to improve efficiency while maintaining full ownership, explainability, and rigor in outputs

Preferred:
Experience in payments, identity, fraud, or financial services
Familiarity with graph databases or graph-based data models
Experience building reusable datasets, pipelines, or executive-level reporting
Experience with observability and application performance monitoring platforms (Dynatrace, Grafana, or similar)

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: $94,000 - $138,000 CAD