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Associate Machine Learning Jobs in Kitchener, ON

Transunion

Principal, Fraud Analytics

Burlington, ON · On-site

Oversee the development of machine learning models, rules engines, and anomaly detection systems to ... We strive to build an environment where our associates are in the driver's seat of their ...

AtHoc

AI Engineering Specialist

Waterloo, ON · On-site

CA$108K - CA$152K/yr

Cloud certifications such asAWS Certified Machine Learning / AI PractitionerorMicrosoft Azure AI Engineer Associate. * Experience embedding Responsible AI, evaluation frameworks, and enterprise ...

Archmill House

Future Opportunities

Ancaster, ON · On-site

Production Roles - Cabinet Makers, Machine Operators, Forklift Operators, Picker/Packers ... Hungry - Who is always looking for more responsibilities and learning * Smart - Who is emotionally ...

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All JobsAssociate Machine Learning JobsAssociate Machine Learning Jobs in Kitchener, ON

Associate Machine Learning information

See Kitchener, ON salary details

$9

$37

$85

How much do associate machine learning jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for associate machine learning in Kitchener, ON is $37.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.80 and $51.58 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 Kitchener, ON?

The most popular types of Machine Learning jobs in Kitchener, ON are:

What cities near Kitchener, ON are hiring for Associate Machine Learning jobs?

Cities near Kitchener, ON with the most Associate Machine Learning job openings:

Associate Machine Learning jobs near you

Principal, Fraud Analytics

Burlington, ON

TransUnion
IT Services • 5 - 10K employees

9.3

Company rating: 9.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Good employer

Respectful managers

Learn new skills

Learn more about TransUnionexternal

Full-time

Re-posted 22 days ago

Job description

TransUnion's Job Applicant Privacy Notice

Team Overview

TransUnion, a global leader in risk and information solutions and one of Canada's major credit bureaus, is seeking a visionary and strategic Principal, Fraud Data & Analytics to lead the evolution of our fraud analytics capabilities. This role is responsible for shaping and executing the fraud data strategy, driving innovation in fraud detection and prevention, and positioning TransUnion as a market leader in fraud intelligence. You will support a high-performing team, influence enterprise-wide decision-making, and represent TransUnion's fraud analytics capabilities to clients, partners, and the broader industry. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Role Overview And Core Responsibilities

As the Principal, Fraud Data & Analytics, you will lead the strategic development and execution of advanced analytics and data-driven solutions to combat fraud across our client portfolio. You will play a pivotal role in shaping our fraud detection capabilities, driving innovation, and delivering measurable value to our partners. Your responsibilities will include:

Strategic Leadership: Define and execute the vision for fraud analytics, aligning with business goals and client needs. Lead cross-functional initiatives to enhance fraud detection, prevention, and mitigation strategies.

Innovation & R&D: Lead the development of advanced fraud detection models using AI/ML, behavioral analytics, and real-time data. Drive research into emerging fraud patterns and new analytical techniques.

Client-Facing Expertise: Serve as a trusted advisor to clients, translating complex fraud trends and data insights into actionable recommendations. Support pre-sales and post-sales engagements with analytical thought leadership.

Data Science & Modeling: Oversee the development of machine learning models, rules engines, and anomaly detection systems to identify and prevent fraudulent activity. Ensure models are explainable, scalable, and continuously optimized.

Product & Platform Collaboration: Partner with product, technology, and data science to embed analytics into our fraud solutions. Influence product roadmaps with data-driven insights and emerging fraud trends.

Performance Monitoring: Establish KPIs and dashboards to monitor fraud trends, model performance, and operational effectiveness. Lead root cause analyses and drive continuous improvement.

Industry Thought Leadership: Stay ahead of evolving fraud tactics, regulatory changes, and technology advancements. Represent the company at industry events, panels, and client forums.

Financial Stewardship: Manage budgets related to fraud analytics tools, data partnerships, and vendor relationships. Provide ROI analysis and business cases for strategic investments.

You will be instrumental in shaping the future of fraud prevention at TransUnion. You will drive innovation, elevate our market presence, and ensure our solutions remain at the forefront of the industry. Your leadership will directly influence product development, client success, and the protection of consumers and businesses across Canada and beyond.


Required Knowledge And Experiences

  • 10+ years of experience in Fraud analytics, data science, and/or financial crime risk, with at least 5 years in a leadership role.
  • 5 + Years of experience in Credit Risk, Collection and/or account management
  • Proven track record of delivering enterprise-scale fraud detection solutions and measurable business impact.
  • Deep expertise in fraud typologies (e.g., 1st, 2nd, 3rd party fraud, identity theft, money laundering), data science, and machine learning.
  • Strong technical proficiency in tools such as Python, R, SQL, and cloud-based data platforms.
  • Exceptional communication and stakeholder management skills, with the ability to influence at all levels, including executive leadership and external clients.
  • Experience presenting at industry conferences or contributing to thought leadership in fraud analytics or financial crime.
  • Advanced degree in a quantitative field such as statistics, mathematics, computer science, or engineering is preferred.

This job posting is for an existing vacancy. The opening is the result of a newly created position.

Accommodation is available, including for applicants with disabilities, in accordance with applicable laws.


TransUnion Overview:

At TransUnion, we encourage and are committed to creating a real, positive impact and shared sense of purpose within our Workforce for Good, which empowers our people to grow, innovate and contribute to a better future for our communities and customers. We strive to build an environment where our associates are in the driver's seat of their professional development- while having access to help along the way. We recognize that success comes when our associates thrive both professionally and personally; that's why we prioritize work/life flexibility and offer resources for our teams across the globe to collaborate and drive excellence.

Be a part of our Workforce for Good - you'll work with great people, pioneering products and cutting-edge technology.


TransUnion's Internal Job Title:

Principal, Product Management

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