1

Data Science Phd Jobs in Ontario (NOW HIRING)

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 ...

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field ... Experience building data science teams from scratch or through periods of rapid growth * Prior work ...

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field ... Established product data science roadmap aligned with business priorities; shipped at least one ...

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

Data Scientist

Ottawa, ON · On-site

$80K - $100K/yr

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

PhD with 1-3 years, MS or MA with 2-6 years, or BS or BA with 4-8 years of data science or quantitative modeling experience * Experience with Fraud, Risk or Financial Crimes * Proficiency in SQL and ...

Manager, Data Science

Toronto, ON · Hybrid

CA$173K - CA$197K/yr

161 Bay Street (93021), Canada, Toronto,Toronto, Ontario, Manager, Data Science About Capital One ... Bachelor's Degree/Master's Degree or PhD in a quantitative field * Experience working with AWS (EC2 ...

Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations ... Experience mentoring Data Scientists and shaping technical standards beyond individual project ...

PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience * 3+ years in Product Analytics, Experimentation and Causal Inference

Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or another related STEM field Experience * 2+ years of hands-on experience in data ...

Degree in a STEM discipline (Data Science, Statistics, Computer Science, or a related quantitative field); a Master's or PhD is preferred but not required. * 3+ years of data science experience ...

Master's or PhD degree in Statistics, Applied Mathematics, Data Science, Computer Science, Engineering, Physics, or a related quantitative field. * 2+ years of industry experience developing and ...

Lead Data Scientist

Mississauga, ON · On-site +1

CA$108K - CA$157K/yr

Master or PhD Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, Computational Linguistic or a related field * 4+ years of experience in Data Science, Machine ...

Lead Data Scientist

Unionville, ON · On-site +1

CA$108K - CA$157K/yr

Master or PhD Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, Computational Linguistic or a related field * 4+ years of experience in Data Science, Machine ...

Lead Data Scientist

Toronto, ON · On-site +1

CA$108K - CA$157K/yr

Master or PhD Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, Computational Linguistic or a related field * 4+ years of experience in Data Science, Machine ...

next page

Showing results 1-20

Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

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

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Ontario?

For Data Science Phd jobs in Ontario, the most frequently searched job titles are:

What cities in Ontario are hiring for Data Science Phd jobs?

Cities in Ontario with the most Data Science Phd job openings:

Infographic showing various Data Science Phd job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Full-time

Re-posted 3 days ago


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