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Associate Machine Learning Jobs in Montreal, QC (NOW HIRING)

Lineage Logistics

Warehouse Associate

Montreal, QC

... machines). * Notifies operational management of any equipment maintenance required. * Reports all ... A career at Lineage starts with learning about our business and how each team member plays a part ...

All JobsAssociate Machine Learning JobsAssociate Machine Learning Jobs in Montreal, QC

Associate Machine Learning information

See Montreal, QC salary details

$9

$39

$91

How much do associate machine learning jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for associate machine learning in Montreal, QC is $39.59, according to ZipRecruiter salary data. Most workers in this role earn between $15.82 and $55.13 per hour, depending on experience, location, and employer.

What does an associate machine learning engineer do?

An Associate Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the supervision of senior engineers. They handle tasks such as data preprocessing, model evaluation, and maintaining machine learning pipelines. Associates often collaborate with data scientists, software engineers, and business teams to ensure that machine learning solutions are integrated effectively into products or services. This role is typically entry-level or early career and is a stepping stone toward more advanced machine learning positions.

What are the key skills and qualifications needed to thrive as an associate machine learning engineer?

To thrive as an Associate Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, usually supported by a relevant degree. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with data processing libraries and version control systems is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration skills help you stand out in this role. These competencies are essential for developing robust models, working efficiently with teams, and delivering impactful data-driven solutions.

What are some common challenges faced by associate machine learning professionals when transitioning from academic projects to real-world business applications?

Associate Machine Learning professionals often find that moving from academic or theoretical projects to business-focused environments introduces new challenges. Real-world datasets can be messy, incomplete, or imbalanced, requiring additional data cleaning and preprocessing. Moreover, business timelines may require rapid prototyping and iterative model development, which is different from the more open-ended nature of academic research. Collaborating with cross-functional teams such as data engineers, product managers, and business stakeholders is also essential to align models with organizational goals. Adapting to these practical aspects is key to succeeding in an Associate Machine Learning role.

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

AspectAssociate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in CS, Statistics, or related; often requires experience with data analysis and programming
Work EnvironmentEntry-level, team-based projects, focused on supporting ML models and data preprocessingMore autonomous, involved in data analysis, model development, and interpretation
Employer & Industry UsageTech companies, startups, research labs; roles in AI and ML teamsWide range of industries including tech, finance, healthcare, and consulting

While both roles involve working with data and machine learning, an Associate Machine Learning typically focuses on supporting ML projects with less experience, whereas a Data Scientist has broader responsibilities including data analysis, model development, and strategic insights. The roles often overlap but differ in scope and experience level.

What are the most commonly searched types of Machine Learning jobs in Montreal, QC?

The most popular types of Machine Learning jobs in Montreal, QC are:

Associate Machine Learning jobs near you

Credit Risk Modelling Senior Associate (Bilingual FR/EN)

PwC

Montreal, QC • On-site

CA$75K - CA$125K/yr

Full-time

Re-posted 9 days ago

PwC rating

8.3

Company rating: 8.3 out of 10

Based on 77 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants

Job description

Line of Service

Assurance

Industry/Sector

Not Applicable

Specialism

Financial Risk

Management Level

Associate

Job Description & Summary

A career in our Financial Services Risk and Regulatory (FS R&R) Credit Risk Modelling practice will provide you with the opportunity to help financial institutions rethink their approach to risk by developing a distinctive strategy and creating capabilities and performance. We play an important part in helping our clients assess, design and develop solutions that not only help them manage risk but also transform risk and complexity into a sustainable advantage.
Our team helps financial institutions with predictive modeling needs, including but not limited to, measure and manage the risk associated with borrowers, counterparties or other third parties who have a financial or contractual commitment to them, expected credit loss measurement (IFRS 9 ECL and CECL), capital measurement/stress testing. As part of the team, you'll help with credit risk modeling, model risk management as well as climate risk modeling for financial institutions.

The Opportunity

AsaCredit Risk Modelling Senior Associate,unlock your potential and embrace the chance to drive meaningful outcomesthat'llelevate your career. Your role will include, butisn'tlimited to:

  • Model development, validation and implementation of Retail and Wholesale credit risk methodologies including obligor and facility risk rating, Basel regulatory capital and economic capital models, allowance for loan and lease loss models (e.g., IFRS9).Assistassurance teams with reviews of clients' model development and validation processes

  • AI and machine learning model development and validation

  • Model risk governance and controls related activities supporting clients in managing model risk across multiple asset classes

  • Collaborate with the team members at various levels to lead and develop compelling client proposals, white papers, thoughtleadershipand points of view, describing the business challenge and proposed business solution on the topics such as GenAI, cloud, climate risk modeling etc.

  • Build andmaintaineffective,trustingand collaborative client relationships

WhatYou'll Bring
Your skills, knowledge, and experiences are what set you apart.Here'swhat we look for:

  • Sufficient experience and exposure to financial services risk practices, credit risk modeling including retail and wholesale credit modeling techniques for adjudication, capital management, and allowance modeling/ or calculations (e.g.IFRS9)

  • Development,implementationand assessment of quantitative credit risk measurement methodologies

  • Solid understanding and knowledge of credit risk processes, credit risk analytics, risk rating methodologies, risk managementpoliciesand risk management organization structures

  • Significant experienceand proven ability in at least one of the following programming languages/softwares: Python, R, SQL, SAS, C++, etc.

  • Master's degree in Economics, Statistics, Mathematics, Physics, Engineering, Financial Engineering, DataScience orother relevant fields would bean asset

  • PRM, FRM or CFA designation would be an asset

  • Proven abilities, especially creative problem-solving, toutilizecredit risk management software,dataandmethodologyin the completion of client engagements, including leveraging related technology vendors and their application

  • Communicationsskillsdemonstratedthrough the ability to write proposals, reports, presentations, etc.

  • Demonstrated ability to manage and prioritize multiple projects

  • A demonstrated commitment to valuing differences and working alongside diverse people and perspectives

  • The successful candidaterequiresfluency in English, in addition to French as they willbe requiredto support or collaborate with English-speaking clients, colleagues and/or stakeholdersduring the course oftheir employment with PwC Canada

This position ensures continuity and upholds our standards of excellence following the departure of a valued team member.

The salary range for this position is $75,400 - $125,400 .The posted salary rangerepresentsthe expected hiring range for PwC locations in major citycentres. Given our national recruiting approach, ranges may vary for positions in other locations. At PwC Canada, base salary isdeterminedby your skills, experience,qualificationsand work location. In addition to base salary, eligible employees may have opportunities toparticipatein variable incentive pay programs which are designed to reward individual and firm-wide achievements.We are committed to offering competitive compensation and adhere to all relevant pay transparency legislation.During the hiring process, our Talent Acquisition team will provide details about our comprehensive total rewards package.

Whyyou'lllove PwC

We'reinspiring and empowering our people to change the world. Powered by the latest technology,you'llbe a part of diverse teams helping public and private clients build trust and deliver sustained outcomes. This meaningful work, and our continuous development environment, will take your career to the next level. We reward your impact, and support your wellbeing, through a competitive compensation package, inclusive benefits and flexibility programs that will help you thrive in work and life. Learn more about our Application Process and Total Rewards Package at:https://jobs-ca.pwc.com/ca/en/life-at-pwc

PwC Canada acknowledges that we work and live across Turtle Island, on the land that is now known as Canada, which are the lands of the ancestral, treaty and unceded territories of the First Nations,Metisand Inuit Peoples. We recognize the systemic racism,colonialismand oppression that Indigenous Peoples have experienced and still go through, and we commit to allyship and solidarity.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Active Listening, Actuarial Science, Communication, Complex Data Analysis, Emotional Regulation, Empathy, Financial Data Mining, Financial Modeling, Financial Risk Analysis, Financial Risk Management, Inclusion, Intellectual Curiosity, Optimism, Presenting Financial Reports, Risk Analysis, Risk Model Implementation, Statistical Analysis Software, Statistical Consulting, Statistical Modeling, Strategic Forecasting, Teamwork, Well Being

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

August 6, 2026We're committed to providing accommodation throughout the application, interview, and employment process. If you require accommodation to be at your best, please let us know during the application process.The use of artificial intelligence (AI) in recruiting is just getting started, so we know you have questions about how and why we use it. At certain points during our recruiting process, we rely on AI to improve your experience. This could be during resume review or curating personalized job recommendations, asking you clarifying questions via a chatbot or during our interview scheduling to improve your experience. Our use of AI helps ensure we combat bias by evaluating candidates equally and fairly, without seeing identity information, such as your name, or gender for example). AI also helps us better predict successful hires by reviewing all applicants for a role and the relationship between your skills, experience and likely success at PwC Canada. While AI supports parts of our recruitment process, final hiring decisions always involve human review. For more information about our use and protection of your data, please refer to our Privacy Policy (https://www.pwc.com/ca/en/privacy-policy.html).Nous tenons a repondre a vos besoins tout au long du processus de demande d'emploi, d'entrevue et d'embauche. Si vous avez besoin de mesures d'adaptation pour etre parfaitement a l'aise, faites-le-nous savoir a l'etape de la demande d'emploi.L'utilisation de l'intelligence artificielle (IA) dans le domaine du recrutement en est a ses balbutiements. Nous savons que vous pourriez vous demander comment et pourquoi nous y avons recours. A certains stades de notre processus de recrutement, nous comptons sur l'IA pour ameliorer votre experience. Par exemple, pendant l'examen du curriculum vit ou l'elaboration d'une liste de recommandations personnalisees, un agent conversationnel pourrait vous demander des precisions ou fixer avec vous un rendez-vous pour l'entrevue. L'IA nous aide a mieux lutter contre les prejuges, car l'evaluation des candidats se fait de facon juste et equitable, sans que les informations d'identification comme le nom ou le sexe soient connues. Elle nous permet egalement de mieux reperer les bons candidats pour un poste et d'evaluer le lien entre leurs competences, leur experience et leurs chances de reussir chez PwC Canada. Bien que l'IA facilite certaines etapes de notre processus de recrutement, les decisions finales d'embauche sont toujours prises par des personnes. Pour en savoir plus sur l'utilisation et la protection de vos donnees personnelles, consultez notre politique sur la protection des renseignements confidentiels (https://www.pwc.com/ca/fr/privacy-policy.html).

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About pwc

Sourced by ZipRecruiter

We know that the future success of our firm is contingent on equitable experiences for our people. From recruitment to partnership, we’re working hard to give every person an equitable opportunity to grow and to thrive as part of our community of solvers. We understand that establishing and maintaining a fair, equitable and welcoming environment for all people requires building a culture of belonging: a shift from awareness to empathy — while demonstrating inclusive leadership that cultivates trust among our people and our clients. PwC is committed to advancing diversity, equity and inclusion (DEI) through an evidence-based strategy designed to achieve well-defined and meaningful aspirational goals. Our aim is to solve problems for the long term, as that is how we build trust and continue to build on our culture of belonging. At the core of this endeavor are stated goals and a series of linked programs enabling targeted interventions at key moments in our employees’ career trajectories.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

London, London, UK

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