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Machine Learning Engineer Data Science Intern Jobs in Brampton, ON

Title and Summary Director, Data Science Overview The Security Solutions Data Science team is ... of machine learning solutions, from data acquisition and feature engineering through ...

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related ... Experience with building and scaling data-intensive software * Experience using GPUs for ...

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

Architect scalable machine learning and Gen AI systems that integrate with existing data platform ... Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related ...

Minimum of 2 years of applicable experience in data science, advanced analytics, machine learning, or AI solution development. * Strong programming capability in Python, R, or similar analytical ...

... machine learning products. High leverage impact -- your work enables Data Science, Product, Engineering, and Risk teams to move faster with reliable, trusted data. Real-world scale and complexity ...

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a ... Understanding of enterprise software integration patterns and data security considerations. * Solid ...

Showing results 41-60

Machine Learning Engineer Data Science Intern information

What does a machine learning engineer data science intern do?

A Machine Learning Engineer Data Science Intern assists in developing and implementing machine learning models and data-driven solutions under the guidance of experienced professionals. The role typically involves data preprocessing, feature engineering, model training, and evaluation. Interns often collaborate with teams to solve real-world problems using statistical analysis and programming. They gain hands-on experience with popular tools and frameworks, such as Python, TensorFlow, and scikit-learn. This internship helps build foundational skills for a future career in machine learning and data science.

What kinds of projects does a machine learning engineer data science intern typically work on, and how are they supported by their team?

As a Machine Learning Engineer Data Science Intern, you will often be assigned to real-world projects such as building predictive models, cleaning and preprocessing data, and assisting with the deployment of machine learning solutions. You’ll collaborate closely with senior data scientists, software engineers, and sometimes product managers, receiving guidance during code reviews and regular team meetings. The environment is typically fast-paced and supportive, encouraging learning through mentorship and hands-on experience. Interns are expected to communicate their findings clearly and contribute to the team’s problem-solving efforts.

What are the key skills and qualifications needed to thrive as a machine learning engineer data science intern, and why are they important?

To thrive as a Machine Learning Engineer Data Science Intern, you need a strong background in mathematics, statistics, and programming (typically Python), supported by coursework or a degree in computer science, data science, or a related field. Familiarity with tools and libraries like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is commonly required. Problem-solving skills, intellectual curiosity, and effective communication make a candidate stand out in collaborative and dynamic environments. These skills are vital for analyzing complex datasets, building reliable models, and clearly communicating insights that drive data-driven decision-making.

Director, Data Science

Toronto, ON • On-site

Full-time

Re-posted 9 days ago


Key responsibilities

  • Define and execute the strategy for solving merchant risk during onboarding and monitoring through the research and development of a merchant registry and profiling capability

  • Build, lead, coach, and develop high-performing teams of Data Scientists, including hiring, mentorship, and performance management

  • Guide the design of scalable machine learning and analytical systems using modern data and cloud platforms, and ensure solutions are validated against both technical and business outcomes


Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, 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

Director, Data ScienceOverview
The Security Solutions Data Science team is responsible for delivering Artificial Intelligence (AI) and Machine Learning (ML) models that support Mastercard's Identity and risk products across the payment networks. These models are designed to be production-ready and to power high-value capabilities that protect digital transactions and enable trusted decisioning at scale.
Beyond model development, the organization is responsible for building scalable, repeatable, and resilient data science capabilities that cover the end-to-end lifecycle of machine learning solutions, from data acquisition and feature engineering through experimentation, validation, deployment, and monitoring. These systems must not only perform effectively in production, but also be built in a way that is industrialized, maintainable, and aligned with broader business and platform needs.
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.
We are looking for a highly skilled and strategic Director to lead a Data Science team that focuses on solving merchant risk during onboarding and monitoring. This role is critical in driving the research and development of a merchant registry and profiling capability within the Identity Data Science portfolio. This includes setting the strategy for how merchant intelligence is built and scaled, guiding the development of reusable data science assets and profiling frameworks, and ensuring strong execution across product, engineering, and data science partners. You will help shape both the technical direction and operational model needed to turn this capability into a durable and scalable advantage.
Role
Key responsibilities include:
Define and execute the strategy for solving merchant risk during onboarding and monitoring through the research and development of a merchant registry and profiling capability
Lead, coach, and develop high-performing teams of Data Scientists, including hiring, mentorship, and performance management
Build a strong team culture focused on collaboration, accountability, and continuous learning
Guide the design of scalable machine learning and analytical systems using modern data and cloud platforms such as Databricks and Sparks.
Establish best practices for problem framing, technique selection, experimentation, and validation across the team
Ensure teams identify appropriate approaches for business problems and rigorously validate solutions against both technical and business outcomes
Partner closely with Product, Engineering, and other stakeholders to translate strategic needs into data science roadmaps and deliverables
Drive Agile delivery practices that support iterative development, measurable outcomes, and continuous improvement
Promote reusable data assets, standardization, and scalable workflows that strengthen long-term execution
Communicate strategy, progress, trade-offs, and business value clearly to senior leadership
Balance long-term vision with near-term delivery to maximize impact and time-to-value
All About You
Essential Skills to be successful:
Advanced degree (Master's or PhD preferred) in Data Science, ML, or related field
Extensive experience leading a Data Science team and drive innovation with inspiration.
Experienced being a great people leader but able to dig into the work where necessary
A proven track record of deploying high performance machine learning models at scale in a production environment
Strong proficiency with Python, SQL, along with experience using scalable Machine Learning and Cloud frameworks
Strong ability to guide teams in identifying appropriate techniques and validating solutions rigorously
Critical thinking and a drive to produce high-quality work, ensuring that all solutions meet rigorous standards
Demonstrated success translating complex business problems into strategic data science initiatives. Ability to lead through ambiguity and change
Strong understanding of Agile methodologies, with the ability to drive iterative delivery across cross-functional teams
Excellent stakeholder management, communication to both technical and non-technical audiences, and leadership skills
Proven ability to build teams, influence roadmaps, and deliver measurable business value in complex environments
High-energy and self-driven orientation
Nice to Have
Experience building or scaling shared data science platforms, registries, or enterprise data assets
Familiarity with merchant risk, fraud, or identity ecosystems
Experience driving cross-team standardization and reusable capabilities
Exposure to governance frameworks for model validation and AI systemsMastercard 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 is a pipeline posting for future opportunities within our team.

Pay Ranges

Vancouver, Canada: $154,000 - $247,000 CADToronto, Canada: $154,000 - $247,000 CAD