Principal Data Scientist

Mastercard is hiring a Principal Data Scientist in Toronto, Canada. Level rates it ; you can apply on Mastercard.

Level's read on this job

On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch, TensorFlow and scikit-learn.
Level classifies it as a senior role.
Level lists 948 other open roles at Mastercard.

AI in this role

Lead the development and delivery of advanced AI and machine learning solutions for Mastercard's Ethoca product.

PyTorchTensorFlowscikit-learnAzureSnowflakeSpark

computer-visionnlpmachine-learningdeep-learninggenerative-aidata-science

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

Overview:

Mastercard is seeking a Principal Data Scientist to lead the development and delivery of advanced AI and machine learning solutions for Mastercard’s Ethoca product that enhances consumer purchase experiences.

This is a senior technical role, responsible for defining the data science product design, guiding execution across multiple business initiatives, and ensuring solutions are delivered at scale to support chargeback reduction, dispute resolution, and consumer clarity. The successful candidate will combine technical depth with strong cross-functional skills to drive measurable business impact.

Responsibilities:

Leading Engineering Culture
• Design and execute the data science vision and roadmap for the product enhancement, aligning technical initiatives with business priorities and product strategy.
• Lead, mentor, and inspire a high-performing data science team, fostering a culture of technical excellence, innovation, and collaboration.
• Partner with product, engineering, and business leaders to shape requirements and deliver data-driven capabilities that improve customer experience and reduce disputes.

Product Impact
• Build and scale AI/ML models that enrich merchant data, enhance transaction clarity, and reduce chargeback/dispute rates.
• Guide the design and implementation of solutions that leverage generative AI, multi-agent systems, NLP, and computer vision to enhance purchase experiences.
• Monitor and continuously improve deployed models to ensure accuracy, reliability, and compliance in a regulated financial environment.

Technical & Operational Excellence
• Provide hands-on technical leadership in model development, deployment, and governance across cloud environments (Azure, Snowflake, Spark).
• Ensure compliance with Mastercard’s data governance, security, and privacy requirements.
• Review and oversee code, models, and engineering components developed by the team to maintain enterprise-grade standards.

Innovation & Thought Leadership
• Drive exploration of cutting-edge technologies, including generative AI and agentic frameworks, to strengthen the product offering and Mastercard technical competence.
• Represent Mastercard’s AI leadership through patents, publications, conference presentations, and academic partnerships.
• Incubate prototypes and proofs-of-concept to evaluate new methods before scaling into production.

All About You:

• Proven experience leading data science teams and delivering enterprise-scale AI/ML solutions.
• Deep expertise in supervised, unsupervised, and generative AI methods, with strong understanding of their mathematical foundations.
• Hands-on background in NLP, information extraction, or computer vision or multi-modal AI applied to real-world business challenges.
• Strong track record of translating complex data problems into scalable, measurable business outcomes.
• Proficiency in Python, ML frameworks (Scikit-learn, PyTorch, TensorFlow), SQL, Spark, and Azure ML/Snowflake.
• Experience working in highly regulated industries, with an emphasis on data governance and compliance.
• Skilled at engaging with senior stakeholders, presenting technical results to diverse audiences, and driving alignment across functions.
• Master’s degree required; PhD preferred.

Nice to Have:
• Experience in payments, FinTech, or consumer transaction data.
• Prior patents or publications in AI/ML.
• Demonstrated success applying GenAI or multi-agent systems in production environments.

#AI

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

How we rate this

Principal Data Scientist at Mastercard rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal Data Scientist is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Toronto, Canada (Ethoca).
The job was posted on July 30, 2026.
Seniority: senior.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPMachine learningDeep learningGenerative AIData SciencePyTorchTensorFlow

Also common in data scientist jobs at this level

LLM AWS Deep learning RAG MLOps Google Cloud

Pay

Typical data scientist job: $168k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where generative ai was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, Machine learning, Deep learning, and Generative AI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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