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Entry Level Data Scientist Machine Learning Jobs in Ontario

Partner with data scientists, engineers, and business stakeholders to gather requirements and ... Machine Learning Expertise:Strong knowledge of machine learning algorithms, with experience ...

New

Junior Machine Learning Engineer

Waterloo, ON · On-site

CA$80K - CA$95K/yr

As a Junior Machine Learning Engineer on the Global AI Team, you will support the design ... You will work with data scientists, engineers, product teams, and business stakeholders to help ...

Graduate degree in Computer Science with a strong background in machine learning required. * Strong problem-solving abilities, solid background in algorithms and data structures required. * Strong ...

Build,validate, and deliver analytics and machine learning solutions that translate complex data ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Build,validate, and deliver analytics and machine learning solutions that translate complex data ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Build,validate, and deliver analytics and machine learning solutions that translate complex data ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Research Machine Learning Scientist

Toronto, ON · On-site

CA$140K - CA$250K/yr

As a Research Machine Learning Scientist, you will * Join a world-class team of machine learning researchers with an extensive track record in both academia and industry. * Research, develop, and ...

... Data Scientist in AdTech, you will design, build, and deploy production-grade machine learning ... Develop, build, and iterate on advanced machine learning models across core adtech domains to ...

Applied Machine Learning Scientist I

Toronto, ON · On-site

CA$105K - CA$125K/yr

Additional We're looking for a highly motivated Applied Machine Learning Scientist to join our AI2 ... In this role, you'll drive the development and deployment of ML solutions that power data-driven ...

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Minimum three years of experience delivering major data science projects in large, complex ... Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture ...

Data Scientist II

Markham, ON · On-site +1

CA$81K - CA$115K/yr

Build machine learning models (e.g., XGBoost, regression models) to improve decision-making ... In-depth knowledge of data science tools such as NumPy, pandas, matplotlib or R equivalent

Showing results 21-40

Entry Level Data Scientist Machine Learning information

What is an entry level data scientist machine learning?

Entry level data scientist machine learning jobs are positions for individuals who are new to the field of data science and machine learning. These roles typically focus on working with data, building and testing machine learning models, and supporting more experienced data scientists. Entry level professionals may clean and analyze data, implement basic algorithms, and help interpret results to inform business decisions. These jobs often require proficiency in programming languages like Python or R, foundational knowledge of statistics, and some experience with machine learning libraries.

What are the key skills and qualifications needed to thrive as an entry level data scientist machine learning?

To thrive as an Entry Level Data Scientist in Machine Learning, you need a solid background in statistics, programming (Python or R), and foundational machine learning concepts, typically supported by a relevant degree in computer science, data science, or a related field. Familiarity with tools and libraries such as scikit-learn, TensorFlow, Pandas, and SQL, as well as experience with data visualization platforms, is highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly set candidates apart. These skills are essential for effectively analyzing data, building predictive models, and translating complex results into actionable business insights.

What are some common challenges faced by entry level data scientists working with machine learning models?

Entry-level data scientists often encounter challenges such as cleaning and preparing messy or incomplete datasets, selecting appropriate algorithms for specific problems, and tuning model parameters to achieve optimal performance. In addition, they may need to clearly communicate technical findings to non-technical stakeholders and collaborate closely with team members from engineering, product, and business departments. Gaining experience in version control, reproducibility, and model deployment are also important steps in mastering the end-to-end machine learning workflow.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Ontario?

The most popular types of Data Scientist Machine Learning jobs in Ontario are:

What are popular job titles related to Entry Level Data Scientist Machine Learning jobs in Ontario?

For Entry Level Data Scientist Machine Learning jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Scientist Machine Learning jobs in Ontario look for?

The top searched job categories for Entry Level Data Scientist Machine Learning jobs in Ontario are:

What cities in Ontario are hiring for Entry Level Data Scientist Machine Learning jobs?

Cities in Ontario with the most Entry Level Data Scientist Machine Learning job openings:

Infographic showing various Entry Level Data Scientist Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Manulife

Toronto, ON

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


Job description

Manulife's bold ambition is to become a digital, customer-first leader. To achieve this, we've made significant investments in Advanced Analytics and AI capabilities.

We are seeking an innovative and experienced Machine Learning Engineer to join our AI + Data team, a cross-functional group spanning Operations, Technology, and Marketing. Our team's mission is to research, build, and deliver production-grade machine learning and Generative AI capabilities that help us better understand our customers, personalize experiences, and drive measurable business impact across insurance, banking, and wealth management globally.

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and reusable patterns that take models from experimentation to production at scale. You will work with large-scale, diverse datasets including call center transcripts, insurance claims, digital transactions, and more, building systems that enhance the end-to-end customer experience.

This is a global role with exposure to markets in Canada, the U.S., and Asia, offering the opportunity to collaborate with cross-functional teams and deliver robust, scalable ML systems across multiple business segment

Position Responsibilities:

  • Reusable Patterns and Accelerators:Build reusable patterns for data, ML, and GenAI workloads, following MLOps, LLMOps, and AIOps best practices, and partner with delivery teams on implementation.
  • CI/CD: Own the engineering backbone for ML delivery, including source control workflows, build and deployment pipelines, automated testing, spec-driven development, and release management.
  • Infrastructure as Code:Provision and manage PaaS infrastructure using Terraform, with repeatable, version-controlled environments across development, staging, and production.
  • Credential and Secrets Management:Implement secure credential handling using Azure Key Vault and managed identities, scoping access narrowly across services and pipelines.
  • Scalable Infrastructure:Develop and maintain scalable ML platforms andservinginfrastructure that support training, inference, monitoring, and lifecycle management of models in production.
  • Data Pipeline Optimization:Partner with data engineers to build high-quality, well-testedfeatureand training pipelines that ensure efficient, reliable data processing for ML applications.
  • Model Development and Deployment:Design, train, evaluate, and deploy machine learning models, and integrate large language models where they are the right tool, to solve complex business problems and improve operational efficiency.
  • Model Performance and Reliability:Continuously monitor and improve models and systems for accuracy, latency, cost, drift, and reliability, with clear observability and alerting.
  • Governance and Responsible AI:Ensure interoperability, data consistency, and responsible AI through strong API and data standards, metadata management, security-by-design, privacy controls, and model governance.
  • Integration and Collaboration:Partner with data scientists, engineers, and business stakeholders to gather requirements and integrate ML solutions smoothly with existing systems.
  • Innovation and Research:Stay current with emerging technologies and practices across data engineering, machine learning, and Generative AI, including RAG, vector search, model fine-tuning, and orchestration frameworks.

Required Qualifications:

  • Professional Experience:At least 4 years of experience in machine learning engineering, with a proven track record of building and deploying ML models and systems in production.
  • Technical Proficiency:Strong programming skills in Python with hands-on experience in ML frameworks and libraries.Experience with Java or Scala for model serving and JVM-based pipelines is an asset, as is familiarity with GenAI tooling such as LangChain, LangGraph, or the OpenAI SDK.
  • MLOps and CI/CD:Practical experience with model lifecycle tooling (for example MLflow, Azure Machine Learning, or Databricks) and with CI/CD pipelinesusing tools such as Jenkins, GitHub Actions, or Azure DevOps.
  • Cloud and Infrastructure:Working knowledge of cloud platforms, containerization (Docker, Kubernetes), and infrastructure as code with Terraform.
  • Educational Background:Bachelor's degree in Computer Science, Engineering, Statistics, or a related field. Equivalent technical experience is also considered.

Preferred Qualifications:

  • Machine Learning Expertise:Strong knowledge of machine learning algorithms, with experience adapting pre-trained and foundation models to domain-specific problems.
  • Large-Scale Data Processing: Experience with distributed computing frameworks such as Spark, and with lakehouse architectures on Databricks or equivalent, including Delta and Unity Catalog for data and model governance.
  • Data Engineering Skills: Solid understanding of data engineering principles, including data pipelines and ETL processes.
  • Problem-Solving Ability: Exceptional problem-solving skills with the capacity to tackle complex technical challenges.
  • Effective Communication: Excellent communication skills to effectively collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders.

When you join our team:

  • We'll empower you to learn and grow the career you want.
  • We'll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
  • As part of our global team, we'll support you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Hybrid

Salary range is expected to be between

$94,430.00 CAD - $144,430.00 CAD

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.

Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact hr@manulife.com for more information about U.S.-specific paid time off provisions.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.