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Scientific Machine Learning Jobs in Quebec (NOW HIRING)

Ce poste se situe a l'intersection de la Data Science, du Machine Learning et de l'ingenierie, avec pour objectif de stimuler l'experimentation, d'optimiser l'experience client et de developper des ...

About the role Intact is looking for a Data Scientist to turn complex data into practical solutions ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

About the role Intact is looking for a Data Scientist to turn complex data into practical solutions ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

Strong understanding of machine learning and statistical modelling techniques. * Proficiency in Python and common scientific computing libraries. * Strong writing skills, with the ability to draft ...

Apply statistical or machine learning knowledge to specific business problems and data. * Develop ... Use data science techniques to find data patterns, anomalies, and optimization opportunities.

We are seeking a senior machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to solve ...

D. degree in Artificial Intelligence, Machine Learning, Data Science, or a related field. * You have at least 5 years of relevant experience in data science or a similar role. * You have strong ...

... applied machine learning * Proven experience leading ambiguous, high-impact data science initiatives from framing through production business impact * Strong experience in at least three of ...

Showing results 21-40

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Quebec?

For Scientific Machine Learning jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Quebec look for?

The top searched job categories for Scientific Machine Learning jobs in Quebec are:

Infographic showing various Scientific Machine Learning job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Full-time

Life, Retirement

Re-posted 19 days ago


Job description

Our employees are at the heart of everything we do. Together, we help people, businesses, and society prosper in good times and be resilient in bad times.


Our employee promise represents Intact's commitment to you in exchange for living our Values, striving to do your best work, being open to change and investing in your career. In return, we promise to provide support, opportunities and performance-led financial rewards at a workplace where you can shape the future, win as a team and grow with us.

Pay at Intact is about much more than just salary.

  • Flexible work arrangements and a hybrid work model

  • Possibility to purchase up to 5 extra days off per year

  • Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more

  • Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)

Salary range (but not limited to):

118,700 - 145,100

Annual bonus target, based on the base salary, with a potential payout of up to double the target (subject to personal and company performance):

12%

As part of our commitment to Win As A Team, we share our success with employees through our annual bonus plan and Employee Share Purchase Plan (ESPP) - with Intact matching 50% of your net shares.

Our pension offerings provide flexibility and long-term security for our employees beyond their careers. We are one of the few companies offering the opportunity to receive guaranteed income for life via our defined benefit pension plan.

Salary for the candidate will be determined taking into consideration a number of factors including: experience, skills, qualifications, anticipated contribution to role, internal equity, etc. The salary range presented above is based on a 35-hour workweek and would represent a majority of different candidate profiles. However, we encourage candidates who may fall outside of this range to apply as well.


About the role

Intact is looking for a Data Scientist to turn complex data into practical solutions (prediction, segmentation, optimization, automation) and to generate actionable insights.

Within the Data Lab, you will work in a modern data ecosystem with multidisciplinary teams (data science, analytics, engineering, product) on high-impact end-to-end use cases (anomaly detection, personalization, experimentation, etc.).

The Lab emphasizes rigor (quality, validation, performance monitoring, continuous improvement), collaboration with business and engineering teams, and value-driven innovation, including generative AI and LLMs to speed up access to information, automate processes, and deliver responsible, measurable solutions in production.

What you'll do here:

  • Develop innovative solutions: Use machine learning and advanced statistical methods to identify trends and patterns in complex datasets.

  • Data transformation: Turn complex databases into actionable insights and recommendations that can guide business strategy.

  • Stay up to date: Keep abreast of the latest trends and methodologies in data science and integrate them into your work.

  • Tool and platform maintenance: Help maintain and improve our data mining tools and platforms to ensure their efficiency and reliability.

  • Actionable recommendations: Provide strategic recommendations based on data analysis to support decision-making processes.

  • Cross-functional collaboration: Work closely with other departments to promote the adoption of data-driven decision-making across the organization.

  • Quality assurance and mentoring: Validate the quality of analytical approaches and deliverables produced by the team to ensure high standards, while coaching less experienced members.

  • Technical leadership: Take on a technical leadership role, guiding the team on best practices in data science and identifying research and development opportunities.

What you bring to the table:

  • A master's degree in a relevant field (mathematics, science, engineering, operations research, economics, statistics, AI, computer science, or a related discipline), or an equivalent combination of education and experience.

  • At least 5 years of experience in data science, machine learning, and advanced statistics applied to solving business problems.

  • Machine learning expertise: Expert-level understanding of machine learning theories and methodologies.

  • Specialization: Expertise in one or more areas such as computer vision, natural language processing, or artificial intelligence.

  • Technical skills: Experience delivering to production across multiple platforms using the following commercial and open-source data mining frameworks and tools: R, Python, GitHub.

  • Team spirit: Strong enthusiasm for collaborative teamwork.

  • Problem-solving: Ability to tackle loosely defined problems with creative and innovative solutions.

  • Communication skills: Excellent written and verbal communication skills, with the ability to convey complex information to non-technical stakeholders.

  • Time management: Strong organizational and time-management skills to handle multiple projects and meet deadlines.

  • Bilingual (French and English): Need to interact on a regular basis with an English-speaking clientele and colleagues across the country.

  • No Canadian work experiencerequiredhowever must be eligible to work in Canada

#LI-Hybrid

Il s'agit d'un nouveau role au sein de notre equipe en pleine croissance | This role is a new member of our growing team.


We are an equal opportunity employer

At Intact, our Value of respect is founded on seeing diversity as a strength. We strive to create an accessible workplace where employees feel valued, included and encouraged to share their unique perspectives.

We encourage applications from individuals who are members of equity-deserving groups, including but not limited to women, Indigenous peoples, persons with disabilities, Black people, and members of the 2SLGBTQI+ community.

As part of Intact's commitment to reconciliation, we acknowledge that we work, meet and travel across the land currently called Canada, originally inhabited by First Nations, Metis and Inuit people. This history extends through many centuries and continues to evolve today.

We have policies to ensure equal access and participation for people with disabilities, including providing workplace adjustments (accommodations). A copy of applicable policies is available on request.

If we can provide a specific adjustment to make the recruitment process more accessible for you, please let us know when we reach out about a job opportunity. We'll work with you to meet your needs.

Learn more about our recruitment process and your candidate journey here.

Please note that Intact does not provide sponsorship or other support for immigration-related matters including but not limited to employer-specific closed work permits. Candidates must be eligible to work in Canada from the anticipated start date and throughout their employment and are solely responsible for maintaining their work eligibility.

If you are an employee of Intact or belairdirect, please apply for this role on Internal Career Site.