Application Deadline:
Address:
33 Dundas Street WestJob Family Group:
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.
- 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:
Pay Type:
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
About Us
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.
As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. 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.
To find out more visit us at https://jobs.bmo.com/ca/en.
BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.
Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.
Skills Required
- Deep understanding of machine learning and deep learning algorithms, including model development, validation, optimization, deployment, and monitoring.
- Experience building, deploying, and maintaining production-grade machine learning solutions at scale.
- Experience developing machine learning models and evaluating emerging technologies and tools for business solutions.
- 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 across data science, engineering, product, and business teams.
- 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, or an equivalent combination of education and experience.
BMO Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BMO and has not been reviewed or approved by BMO.
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Parental & Family Support — Paid parental leave up to 16 weeks at full pay for all new parents, plus up to $20,000 for adoption, surrogacy, and fertility, and 10 days of paid backup childcare indicate robust family support. These elements stand out within BMO’s U.S. package.
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Retirement Support — A 401(k) design combining a core employer contribution with dollar-for-dollar matching up to a set portion of pay, plus immediate vesting on match and employee contributions, signals strong retirement funding. The core contribution’s three-year vesting is clearly defined.
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Leave & Time Off Breadth — Vacation accrual scales with grade and service, alongside 9–10 paid holidays and additional paid time off buckets (bereavement, school activities, civic duties, blood donation, volunteering). This breadth offers multiple avenues for time away beyond standard vacation.
BMO Insights
What We Do
At BMO, banking is our personal commitment to helping people at every stage of their financial lives. The truth is, people’s needs change: so we change too. But we never change who we are. Which means we’ll never waiver from providing our customers the best possible banking experience in the industry. Our incredible team of over 46,000 people is just the tip of the iceberg. You should get to know us. We’re here to help.
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