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Data Science Research Assistant Jobs in Toronto, ON

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 ...

Data Scientist

Toronto, ON

CA$68K - CA$100K/yr

Research and stay updated with the latest advancements in data science and AI technologies * Ensure AI models have proper documentation and model transparency and that they adhere to responsible AI ...

Research Assistant

Mississauga, ON ยท On-site

CA$33/hr

We are seeking a Research Assistant to conduct complex data analysis. This person will be involved in various aspects of projects from concept and story writing to the coding, programming and ...

New

Research Assistant Level II

Toronto, ON ยท On-site

CA$47K - CA$59K/yr

Enter data accurately for sample collection, processing, storage/shipment, and analysis ... Bachelor's degree in Sciences preferred. * Preferred: CRO industry experience. * Minimum of 2 years ...

Data Scientist

Woodbridge, ON

CA$85K - CA$115K/yr

... will assist the Director of Data Science and other key stakeholders in bringing actionable data ... Well-developed business analysis, research and creative problem-solving skills. * Organizational ...

The Sr. Data Scientist will assist the Director of Data Analytics and other key stakeholders to ... Research preferred. * 6+ years working experience with data science techniques: clustering ...

About the team Our Data Science team partners deeply with teams across Stripe to ensure that our ... You'll work closely with Fraud Engineering and Risk Operations to move models from research to ...

Data Science and Machine Learning * Translate business goals into analytical problems ... Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques ...

Data Science and Machine Learning * Translate business goals into analytical problems ... Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques ...

Data Science and Machine Learning * Translate business goals into analytical problems ... Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques ...

Data Science and Machine Learning * Translate business goals into analytical problems ... Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques ...

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Data Science Research Assistant information

See Toronto, ON salary details

$15.7K

$79.7K

$183.7K

How much do data science research assistant jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data science research assistant in Toronto, ON is $79,723.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,650.00 and $117,861.00 per year, depending on experience, location, and employer.

What does a data science research assistant do?

A Data Science Research Assistant supports research projects by gathering, cleaning, and analyzing data using statistical and computational techniques. They assist senior researchers with designing experiments, developing models, and interpreting results. Typical tasks include data preprocessing, coding in languages like Python or R, literature reviews, and creating visualizations to summarize findings. Their work helps advance scientific knowledge and inform decision-making based on data-driven insights.

What are the key skills and qualifications needed to thrive as a data science research assistant?

To thrive as a Data Science Research Assistant, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, statistics, or related fields). Familiarity with tools such as Python, R, Jupyter Notebooks, and data visualization libraries as well as experience with version control systems like Git is typical, and coursework or certifications in data science can be beneficial. Attention to detail, problem-solving ability, and strong communication skills are essential to effectively analyze data, interpret results, and collaborate with research teams. These skills and qualities are critical for producing reliable insights, supporting research objectives, and ensuring the integrity of data-driven projects.

How does a data science research assistant typically collaborate with other team members during a research project?

Data Science Research Assistants frequently work alongside data scientists, research leads, and subject matter experts to support ongoing research. Their responsibilities often include cleaning and preprocessing data, performing exploratory analyses, and implementing models. Regular collaboration occurs through team meetings, code reviews, and sharing findings, ensuring alignment with project goals. Open communication and adaptability are essential, as priorities and datasets can shift based on project needs.

What is the difference between Data Science Research Assistant vs Data Analyst?

AspectData Science Research AssistantData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or higher in Data Analysis, Statistics, or related field
Work EnvironmentResearch labs, academic institutions, or research-focused organizationsBusiness settings, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutes, government agenciesCorporations, marketing firms, finance, healthcare
Common Search & ComparisonYesNo

Data Science Research Assistants typically focus on supporting research projects through data collection, analysis, and modeling in academic or research settings. Data Analysts primarily interpret data to help organizations make business decisions. While both roles require strong analytical skills and knowledge of data tools, the research assistant role emphasizes academic research and experimentation, whereas data analysts focus on business insights and reporting.

What are popular job titles related to Data Science Research Assistant jobs in Toronto, ON?

For Data Science Research Assistant jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Data Science Research Assistant jobs in Toronto, ON look for?

The top searched job categories for Data Science Research Assistant jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Data Science Research Assistant jobs?

Cities near Toronto, ON with the most Data Science Research Assistant job openings:

Infographic showing various Data Science Research Assistant job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $79,723 per year, or $38.3 per hour.

Director, Data Science

MasterCard

Toronto, ON โ€ข On-site

Full-time

Re-posted 5 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