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Data Science Degree Jobs in Quebec (NOW HIRING)

Graduate degree is considered an asset. 5+ years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields. Nice to Have Experience working in ...

Bachelor's degree in data science, engineering, computer science, statistics, or a related field. Years of experience: 2 to 3 years of experience in a similar role. Technical skills: * Excellent ...

$120 - $180/hr

... Data Science leadership to ensure the platform accelerates DS velocity rather than introducing process frictionRequired QualificationsEducationMaster's degree in Computer Science, Engineering ...

Bachelor's degree in computer science, Software Engineering or any equivalent combination of training and experience. * 4+ years experience in Software Engineering / Data Engineering / ETL ...

Bachelor's degree in BusinessAnalytics,Information Systems, Engineering,Data Science,ora relatedfield. * Minimum2years of experience in a data analyst, product data, or master data management role.

Bachelor's or graduate degree in computer engineering, mathematics, data science, or related disciplines. * 4-6 years of professional experience in a related field. * Experience using the following ...

Bachelor's or graduate degree in computer engineering, mathematics, data science, or related disciplines. * 4-6 years of professional experience in a related field. * Experience using the following ...

Data Engineer

Montreal, QC · On-site

  • Retirement

  • PTO

... or Master's degree in Computer Engineering, Software Engineering, Computer Science, or an ... Data Fundamentals Solid understanding of ETL/ELT patterns, data modeling, partitioning strategies ...

Data Engineer

Montreal, QC · On-site +1

CA$80 - CA$85/hr

... Degree in Computer Science, Business Intelligence or equivalent Solid and demonstrated experience on following technologies: Snowflake DBT Microsoft SQL Server Power BI Git Fluent in various ...

University degree in Computer Science, Engineering, or a related field. Relevant Experience * Minimum of 5 years of industry experience in development, coding, scripting, and data-oriented design.

Showing results 41-60

Data Science Degree information

What is the difference between Data Science Degree vs Data Analyst?

AspectData Science DegreeData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's in Statistics, Mathematics, or related fields
Work EnvironmentResearch, modeling, developing algorithms, often in tech or finance industriesData cleaning, reporting, visualization, supporting business decisions
Employer & Industry UsageTech companies, finance, healthcare, academiaRetail, marketing, finance, healthcare

Data Science Degree programs focus on advanced analytics, machine learning, and programming, preparing individuals for complex modeling roles. Data Analysts typically handle data processing, visualization, and reporting to support decision-making. While both roles require strong analytical skills, Data Science degrees emphasize technical and statistical expertise, whereas Data Analysts focus on interpreting data for business insights.

What is a data science degree?

A Data Science degree is an academic program that prepares students to analyze, interpret, and derive insights from complex data sets using statistical, computational, and machine learning techniques. The curriculum typically includes coursework in mathematics, statistics, computer science, and specialized data science methods. Graduates are equipped with the skills to work in a variety of industries, tackling real-world problems by leveraging data-driven decision making. This degree can be pursued at the undergraduate or graduate level, and often includes hands-on projects and internships.

What types of real-world projects or team collaborations can I expect to work on after earning a data science degree?

After earning a Data Science degree, you can expect to engage in a variety of real-world projects such as building predictive models, analyzing large datasets to uncover business insights, and developing data-driven solutions for organizational challenges. Data scientists often collaborate closely with cross-functional teams, including software engineers, business analysts, and domain experts, to translate complex data findings into actionable strategies. These collaborations not only enhance your technical skills but also provide valuable experience in communication and project management, which are essential for career growth in this field.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in mathematics, statistics, and programming, typically supported by a degree in data science, computer science, or a related field. Proficiency in technical tools such as Python or R, SQL, and machine learning frameworks, along with relevant certifications, is highly valued. Strong problem-solving abilities, effective communication, and curiosity help set apart top-performing data scientists. These skills are crucial for extracting actionable insights from data, collaborating with stakeholders, and driving data-driven decision-making.

What are popular job titles related to Data Science Degree jobs in Quebec?

For Data Science Degree jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Data Science Degree jobs in Quebec look for?

The top searched job categories for Data Science Degree jobs in Quebec are:

Infographic showing various Data Science Degree job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Applied Machine Learning Scientist II

Td

Montreal, QC • On-site

CA$125K - CA$154K/yr

Full-time

Posted 11 days ago


Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$125,500 - $154,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In this role, you'll apply expertise across the end-to-end AI and machine learning lifecycle, including model development, evaluation, testing, validation, deployment, and monitoring for both traditional machine learning and Generative AI solutions. You'll work closely with business, technology, risk, governance, and implementation partners to bring AI capabilities to life and deliver measurable business impact.

This role offers an excellent opportunity to combine hands-on machine learning expertise with broader responsibilities related to AI solution assessment, vendor model evaluation, implementation, and governance. You will be expected to work with multiple business partners to advance the use of Machine Learning and AI at TD while supporting the responsible adoption of both internally developed and third-party AI solutions.

KEY ACCOUNTABILITIES

Develop, deploy, and maintain Predictive and Generative AI solutions for use cases such as Agentic AI, LLM-based models, Pricing, and Anomaly Detection.
Lead the evaluation, implementation, testing, monitoring, and ongoing lifecycle management of both internally developed and third-party AI/ML solutions.
Assess vendor-provided and out-of-the-box AI models, including their capabilities, limitations, performance characteristics, implementation considerations, and governance implications.
Translate business problems into analytical frameworks and collaborate with cross-functional teams to define success metrics, testing methodologies, and solution approaches.
Conduct rigorous model evaluation, documentation, A/B testing, validation support, and monitoring to ensure model performance, fairness, stability, and compliance with Responsible AI principles.
Communicate complex technical results to technical and non-technical stakeholders and provide actionable recommendations regarding model performance, implementation, and risk.

JOB REQUIREMENTS

Communication & Relationship Skills
Excellent written and verbal communication.
Comfortable and effective when interacting with a wide range of business partners and stakeholders.
Ability to develop and maintain strong internal relationships across business, technology, risk, and governance functions.
Ability to translate complex technical concepts and analytical findings into clear business language.

Strategic Thinking & Judgment
Creative, out-of-the-box thinker with strong conceptual and problem-solving skills.
Motivated to constantly identify innovative ways to enhance analytical solutions and AI implementation practices.
Capable of quickly identifying drivers of model performance variation, implementation risks, and monitoring concerns.
Ability to evaluate internally developed and vendor-provided AI solutions while balancing business value, performance, and governance requirements.

Technical Competencies
Proficiency in Python and modern machine learning frameworks and tools.
Experience developing, evaluating, and deploying machine learning and Generative AI solutions.
Strong understanding of model evaluation methodologies, experimentation, statistical testing, and performance monitoring.
Experience with structured and unstructured data, feature engineering, and model interpretability techniques.
Exposure to LLMs, agentic AI systems, and practical Generative AI applications.
Familiarity with model governance, Responsible AI principles, model validation, and model risk management practices.
Experience with SQL, Azure Cloud, Azure ML Services, or Databricks is an asset.

Education & Experience

Undergraduate degree in Science, Technology, Engineering, Mathematics, Economics, Finance, or a related quantitative discipline.
Graduate degree is considered an asset.
5+ years of relevant experience in machine learning, advanced analytics, data science, model evaluation, or related fields.

Nice to Have

Experience working in financial services or regulated environments.
Familiarity with model validation, model risk management, governance, or audit processes.
Experience evaluating vendor-provided analytical solutions, AI platforms, or commercial Generative AI products.
Familiarity with causal inference, anomaly detection, or agentic AI systems.

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We're delighted that you're considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. You'll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you've got everything you need to succeed in your new role.

Interview Process
We'll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.


Accommodation
Your accessibility is important to us. Please let us know if you'd like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
We look forward to hearing from you!

Language Requirement (Quebec only):

Maitrise d'une langue autre que le francais pour offrir du soutien ou traiter avec des employes ou des collegues qui ont besoin de services et de soutien dans une langue autre que le francais.