Principal Data Scientist​ - R&D Job Listing at Mastercard in Toronto, ON (Job ID R-274571)

Description

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

Principal Data Scientist​ - R&D Overview
We are looking for a talented Principal 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:
• Architects, designs and develops advanced machine learning models, predictive algorithms, and statistical solutions to solve complex business challenges, ensuring alignment with Mastercard's strategic goals and technical standards.
• Communicates complex insights and data solutions effectively to both technical and non-technical stakeholders, including senior leadership, by drawing upon sophisticated data analysis, visualization, and feature engineering.
• Leads and influences high-priority data science initiatives, guiding teams on best practices regarding statistical hypothesis testing, data cleaning, and organization of large, complex datasets to uncover meaningful data patterns and trends.
• Innovates with complex data structures, modeling techniques, and parameter tuning to contribute to thought leadership initiatives by optimizing model performance, validating results with cross-validation and other metrics.
• Collaborates with senior AI/ML engineers and cross-functional teams to facilitate the scaling, deployment, and operationalization of models into production environments, ensuring adherence to technical best practices and quality standards.
• Contributes to Mastercard's intellectual capital and capability development by recommending areas of opportunity for methodological innovation and process improvements.
• Mentors team members by sharing best practices, innovative techniques, and emerging trends to develop expertise and capabilities around their discipline.

All About You:
• Expertise in architecting and creating production grade systems using various Machine Learning, Deep Learning and NLP concepts and models for both supervised and unsupervised learning.
• Proficiency with Python and related ecosystem of Data Science tools and packages including numpy, pandas, sklearn, spacy, keras, torch, transformers, langgraph.
• Sound Working Knowledge of optimization algorithms like Gradient Descent, its variants and related ecosystem of concepts like learning rates, batch sizes, loss functions and regularization strategies.
• Working knowledge of Python based API based frameworks like FastAPI and comfortable working with JSON objects.
• Good working knowledge of pyspark with conceptual understanding of parallel processing for huge data volumes.
• Expertise in applying various Statistical techniques and foundational concepts including different types of Hypothesis Testing.
• Expertise in creating solution architectures and pipelines.
• Experience in creation of Agentic AI applications using frameworks like langgraph and knowledge of Agentic AI design patterns and related concepts like Context Management, LLMOps, AgentOps, Guardrails, Agent Validation and Evaluation.
• Familiarity with Prompt engineering and working with both closed source models and open-source models.
• Working knowledge of MLOps tools like MLflow.
• Working Knowledge of LLM Finetuning is good to have.
• Strong hands-on experience in creating and executing optimized SQL queries and creating stored procedures with databases like Cosmos DB and Postgres DB.
• Experience in code configuration management with frameworks like github and bitbucket.
• Experience working with Unix commands for accessing various systems and databases and deploying and managing services / APIs.
• Working knowledge of cloud platforms like Azure and using Cloud Native services.
• Working knowledge of Databricks is good to have.

#AI1

#LI-TE1 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 reasonable_accommodation@mastercard.com 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: $154,000 - $247,000 CAD

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