Application Deadline:

08/14/2026

Address:
33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

This is a hybrid role in Toronto

Senior Manager, Machine Learning leverages advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale machine learning solutions.

• End-to-end project management, continuous interaction with key stakeholders (strategy, implementation, business and model validation partners)
• Data mining or extracting usable data from multiple data sources, process, clean, validate the integrity of data to be used for analysis and analyze large amounts of information to find patterns and solutions
• Develop prediction systems through the usage of machine learning tools and advanced statistics to select features, create and optimize classifiers or regression outcome
• Present result in a clear and concise manner for non-technical stakeholders and comprehensive model documentation
• Provide analysis and consultancy on model performance and recommend model usage
• Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to problems that can be complex and non-routine.
• Responsible for resolving issues raised by independent validation, Internal Audit and ongoing model monitoring
• Accountable for existing models in production and responsible for documentation related to existing models (annual assessment and re-validation, model updates)

Qualification

• A post secondary degree in a quantitative field (i.e. mathematics, statistics, computer science, economics, engineering, physics, business); Advanced degree is an asset
• 5+ years of experience building and deploying ML models, with strong understanding and working knowledge of advanced statistical methods and Machine Learning techniques
• 5+ years of experience in data manipulation on large datasets (ingestion, processing, merging and aggregation of data)
• Strong programming skills in Python
• Proficiency in both SQL and Big data technologies (Hadoop, Spark)
• Experience working in cloud based modeling environment a plus (ie. AWS Sagemaker, AzureML, etc)
• Experience in automation and scheduling of data pipeline for end-to-end scoring solutions
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• The ability to present technical concepts and results in an audience-appropriate way
• An inquisitive and investigative nature: You are driven by curiosity and seek answers to problems by sifting through data to discover patterns and customer journeys
• Ability to think outside of the box and work with ambiguity

Salary:

$103,200.00 - $192,000.00

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards