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 - R&D
Overview
We are looking for a talented Lead Data Scientist to join with our Foundry Research and Development team to build innovative products delivered at scale to global markets.
The Foundry Research and Development team is built on a foundation of research and development, mining innovation internally, innovating new product lines with emerging technology, managing new products from inception to market validation and engaging strategically with start-ups to shape the future of commerce with and for our customers.
This team operates across geographies and technology domains, tackling complex challenges to bring innovative payment solutions and services to market.
At Mastercard Foundry, we empower innovation by exploring emerging technologies and building cutting-edge solutions that help define the future of commerce globally.
Responsibilities:
- Leads the technical design, development, and review of complex, scalable machine learning models, predictive algorithms, and statistical solutions to address high-priority business challenges, ensuring alignment with Mastercard’s organizational standards and best practices.
- Guides the refinement and optimization of models and algorithms through feature engineering, hyperparameter tuning, and validation techniques to ensure performance, reliability, and robustness in production environments.
- Collaborates with cross-functional teams, including AI/ML engineering, product, and business stakeholders, to support the deployment, scaling, and operationalization of models while maintaining technical excellence.
- Translates complex data science insights into clear, actionable recommendations to support decision-making and innovation initiatives.
- Contributes to the development and adoption of best practices, standards, and knowledge sharing in statistical analysis, feature engineering, model tuning, and validation.
- Maintains comprehensive technical documentation of models, processes, and methodologies to support reproducibility, knowledge transfer, and continuous improvement.
- Mentors and guides junior team members through hands-on support, reviews, and on-the-job learning to strengthen data science capabilities across the team.
All About You:
- Expertise in designing and delivering production grade machine learning, deep learning, and NLP solutions for both supervised and unsupervised use cases, including solution architectures and end to end pipelines.
- Strong proficiency in Python and the data science ecosystem (e.g., numpy, pandas, sklearn, keras, torch, transformers, langgraph), with experience building and integrating APIs using frameworks such as FastAPI and working with JSON based services.
- Solid understanding of statistical techniques and optimization methods, including hypothesis testing, feature engineering, model tuning, validation, and performance evaluation.
- Experience working with large scale data processing and analytics technologies, including PySpark, SQL (Cosmos DB, Postgres), and parallel data processing concepts.
- Familiarity with modern AI/ML practices such as Agentic AI patterns, prompt engineering, MLOps (e.g., MLflow), and exposure to LLM fine tuning and evaluation approaches.
- Experience working in cloud-based environments, leveraging cloud native services (e.g., Azure), with working knowledge of Databricks, Unix based systems, and code configuration management tools such as GitHub or Bitbucket.
- Passion for building high quality, maintainable code and applying modern software engineering best practices.
- Ability to work independently and lead complex initiatives, while collaborating effectively with cross functional teams and mentoring others in a fast paced, innovative environment.
- Strong communication skills, with the ability to translate complex technical concepts into clear insights and recommendations for a range of stakeholders.
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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
[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 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
