Machine Learning Analyst

Job Description

Please note

• Current work authorization for Canada is required for all openings.

• You will be working on a flexible hybrid schedule as part of Fidelity’s dynamic working arrangement.

• This is a full-time regular opportunity.

• The work location for this role is 483 Bay Street in Toronto until approximately late 2026, when the work location will change to the new Mississauga office at 3 Robert Speck Parkway

Who We Are

At Fidelity, we’ve been helping Canadian investors build better financial futures for over 35 years. We offer individuals and institutions a range of trusted investment portfolios and services - and we’re constantly seeking to find new and better ways to help our clients. As a privately owned company, we boldly embrace innovation in all areas as we continue to grow our business into the future.

Working with us means you’ll be part of a diverse and dedicated group of people who make a real difference for our clients and communities every day. You’ll have a wide range of opportunities to grow and develop your career in an inclusive environment where you’ll feel valued and supported to be your best - both personally and professionally.

Fidelity Investments Canada is looking for a highly motivated and creative ‘Machine Learning Analyst’ to Fidelity Investments Canada is looking for a highly motivated and creative ‘Machine Learning Analyst’ to develop innovative AI/ML solutions to complex business challenges. Critical to the role’s success will be the individual’s penchant for continuous learning and a laser focus on delivering practical applications in a quickly evolving technical environment. As an ML Analyst, you will be collaborating with an interdisciplinary team that leverages large datasets using highly scalable computational resources to deliver end-to-end AI/ML based projects. You will be responsible for conducting exploratory data analysis, data pre-processing and transformation, developing ML algorithms, and assisting with deployment using both on-premise and cloud-based platforms.

What You’ll Do

As an ML Analyst, you will be collaborating with an interdisciplinary team that leverages large datasets using highly scalable computational resources to deliver end-to-end AI/ML based solutions. You will be responsible for conducting exploratory data analysis, data pre-processing and transformation, developing ML algorithms, and assisting with deployment using both on-premise and cloud-based platforms.

• Develop machine learning-based software solutions using open source and proprietary software systems.

• Conduct applied research to identify and understand different algorithms and methods for use case development.

• Collaborate effectively within agile scrum sessions alongside the Emerging Technology, IS ML Ops teams and business stakeholders to develop and implement high-impact business solutions.

• Rapid prototyping of new algorithms/approaches and conducting comparisons with existing algorithms and baselines.

• Iterate on model performance through error analysis, benchmarking, feature refinement, prompt evaluation, and comparison against baseline approaches.

• Assist the IS Infrastructure and IS ML Ops teams in designing customized ML environments as needed.

• Support projects through the documentation, monitoring and version control of models.

• Develop and evaluate Generative AI and Large Language Model solutions, including prompt engineering, retrieval-augmented generation, document intelligence, summarization, classification, and conversational AI use cases.

• Work with enterprise data platforms such as Snowflake to prepare, query, transform, and analyze structured and unstructured data for AI/ML and Generative AI use cases.

• Explore and prototype solutions using Snowflake Cortex and related cloud AI services where appropriate.

What We’re Looking For

• A completed Master’s Degree in Computer Science, Statistics, Software Engineering or other STEM discipline, or equivalent working experience.

• Experience with data collection, data annotation, and active learning.

• Solid theoretical grounding in core machine learning concepts and techniques.

• 2+ years of experience within a data science, artificial intelligence and/or applied machine learning position.

• 1+ year of experience with cloud computing is an asset.

• 1+ year of experience building production machine learning models, and deploying them to solve inference challenges at scale is an asset.

• Strong understanding of machine learning approaches, including predictive modelling, supervised and unsupervised learning, NLP, Generative AI / Large Language Models, and model evaluation.

• AWS Certified Machine Learning and AWS Certified Data Analytics are assets.

• Investment Funds in Canada and/or Canadian Securities Course (CSI) is an asset.

• 1–2 years of experience working with Snowflake, including strong SQL skills, data transformation, query optimization, and familiarity with Snowflake Cortex or other native AI/ML capabilities.

Expands the existing Snowflake requirement.

• Experience using Git for version control, including GitHub, branching, pull requests, and code reviews.

• Practical experience with Generative AI / Large Language Model workflows, such as prompt engineering, retrieval-augmented generation, embeddings, vector search, model evaluation, or orchestration frameworks such as LangChain, LlamaIndex, or similar tools.

• Familiarity with responsible AI practices, including model governance, privacy, explainability, hallucination mitigation, and secure handling of enterprise data.

The Skills You Bring

• Strong communication skills and the ability to work with diverse stakeholders in a team environment.

• Ability to adapt quickly in the face of change using excellent problem-solving skills and creativity.

• Familiarity with popular Python-based AI/ML libraries, such as scikit-learn, PyTorch, pandas, NumPy, matplotlib, and associated workflows.

• Experience with deployment of machine learning model pipelines using AWS, such as SageMaker.

• Familiarity with containerization of ML models, including Docker and Kubernetes.

• Strong SQL skills for querying and transforming data across cloud data platforms and relational databases, including Snowflake and traditional platforms such as Oracle, SQL Server, DB2, or MySQL.

Replaces: “SQL skills for querying relational databases…”

• Demonstrated proficiency with deep learning, ensemble-based methods, NLP, time series analysis, and optimization techniques.

• Familiarity with LLM application development patterns, including prompt design, retrieval pipelines, embeddings, semantic search, and evaluation of generated outputs.

• Ability to translate business problems into practical AI/ML or Generative AI solutions, while balancing technical feasibility, business value, and risk considerations.

Total Rewards That Reflect Your Impact We believe exceptional work deserves exceptional recognition. That’s why we offer a competitive compensation package designed to support your success today—and your financial well-being tomorrow.

For this role, your total rewards include

• Base Salary and Discretionary Performance Bonus: Total annual cash compensation (base salary pus target bonus) ranges from $105,000 to $129,000 , based on your experience and qualifications.

• RRSP Contribution: After 6 months of employment, we invest in your future with an RRSP contribution—no employee matching required.

We’re proud to offer a compensation package that aligns with provincial pay transparency requirements.

Some of the ways we’ll help you feel valued and supported as part of our team:

• Flexible working arrangements - 100% remote, hybrid, and in office options

• Competitive total compensation, including company contributions to your group RRSP without a matching requirement from you

• Comprehensive health benefits that start on your first day, with 10