Application Deadline:

09/29/2026

Address:
33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

This is a hybrid role in Toronto

We are seeking a Senior Data Scientist who combines deep expertise in machine learning with strong software engineering skills and experience building and deploying production-grade ML solutions at scale. In this role, the candidate will leverage advanced machine learning, deep learning, and artificial intelligence techniques to develop models that analyze large volumes of structured and unstructured data, generating actionable insights and business value. The successful candidate will collaborate closely with data scientists, engineers, and analytics teams to optimize, refine, operationalize, and scale analytical solutions into robust, enterprise-grade products.The ideal candidate will also be a technical leader who can mentor team members, promote software engineering and MLOps best practices, improve code quality through design and code reviews, and help drive technical excellence across the team.

Mandatory Qualifications

• Deep understanding of machine learning and deep learning algorithms, including model development, validation, optimization, deployment, and
  and monitoring.
• Experience building, deploying, and maintaining production-grade ML solutions at scale.
• Experience developing machine learning models, and evaluating emerging technologies and tools to deliver innovative data-driven solutions for business stakeholders.
• Strong software engineering fundamentals, including advanced Python development, algorithms, and data structures.
• Experience performing code reviews and promoting coding standards, software design principles, and engineering best practices.
• Hands-on experience with Git, GitHub, version control, and collaborative software development workflows.
• Strong communication and collaboration skills, with the ability to work effectively across data science, engineering, product, and business teams.

Preferred Qualifications (Nice to Have)

• Experience with AWS, SageMaker Unified Studio, lakehouse architectures, PySpark, feature stores, and MLOps platforms.
• Previous experience in banking, fintech, or other highly regulated industries.
• Technical leadership or people management experience, including mentoring and leading cross-functional teams.
• Master's or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related field. Research experience and publications at top-tier conferences such as NeurIPS, ICML, ICLR, KDD, or equivalent venues.
• Typically 5-7 years of relevant experience and a post-secondary degree in a related field of study, or an equivalent combination of education and experience.

Salary:

$80,000.00 - $175,000.00

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