- Employment type
- Full-time · On-site
- Posted
- September 21, 2026
- NOC code
- 21211 — Data scientists
- Province
- Ontario (ON)More in Ontario
Hiring confidence: Sparse posting · 18/100
This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored
Job Overview
This role is based in Ontario. The Canadian NOC code for this position is 21211 — Data scientists. BMO is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in Ontario
Average salary for Data Scientist in Ontario
Median $103,730 per year, with most postings between $103,730 and $156,000 (Data scientists, 2026-05, 37 postings). This posting does not state a salary.
NOC code
21211 — Data scientists. The National Occupational Classification code is what Express Entry, provincial nominee programs and Job Bank use to identify this occupation.
Typical qualifications for Canadian employers
A master's or bachelor's degree in a quantitative field, plus Python or R, statistical modelling and experience shipping models to production.
Licensing: No licence or registration is required.
Fit check
Is this role right for you?
Top skills this posting asks for:
- Data Science
- Data Analytics
- Statistical Analysis
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What you'll do
- Develop and implement data science models and solutions
- Perform statistical analysis on financial and business data
- Create data visualizations and reports for Capital Markets division
- Support data analytics and reporting initiatives
- Collaborate with cross-functional teams in Sales & Service
- Assist in building predictive models for business insights
- Document methodology and findings for stakeholders
- Contribute to Capital Markets' data-driven decision-making processes
What you'll need
- Bachelor's degree in relevant field (Mathematics, Statistics, Computer Science, Economics, or related discipline)
- Strong analytical and problem-solving skills
- Proficiency in programming languages (Python, R, or similar)
- Knowledge of SQL and database management
- Understanding of statistical concepts and machine learning
- Ability to work with large datasets
- Communication skills for translating technical findings to business stakeholders