Data Analytics & Reporting This is a hybrid 12 month contract role in Toronto

We are seeking a Staff 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.

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.

Experience with AWS, SageMaker Unified Studio, lakehouse architectures, PySpark, feature stores, and MLOps platforms.

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.

Salaries for part time roles will be pro-rated based on number of hours regularly worked. 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. It calls on us to create lasting, positive change for our customers, our communities and our people. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

Accommodations are available on request for candidates taking part in all aspects of the selection process. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

📌 Assistant Data-Scientist - Machine Learning H/F (Toronto)
🏢 BMO
📍 Toronto