Data Scientist

Toronto, Ontario

On-site

Full-time

No salary postedToday

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Employment type: Full-time · On-site
Posted: September 20, 2026
NOC code: 21211 — Data scientists
Province: Ontario (ON)More in Ontario

Hiring confidence: Sparse posting · 18/100

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Job Overview

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What it's like to be a Northbridge Data Scientist The Data Science Team is a central partner to the business for Northbridge's predictive and prescriptive capability using applied statistics, machine learning or artificial intelligence to build business solutions. The primary role of Data Scientist 2 is to participate in the data science lifecycle to develop and deploy analytical models. Tackle a breadth of challenges from wrangling data, finding the optimal model fit, to delivering results to …

This role is based in Ontario. The Canadian NOC code for this position is 21211 — Data scientists. Northbridge Financial Corporation 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.

All Data Scientist jobs in Ontario

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What you'll do

Participate in the data science lifecycle
Develop analytical models
Deploy analytical models
Wrangle and prepare data
Find optimal model fit
Deliver results to business stakeholders
Build business solutions using predictive and prescriptive capabilities

What you'll need

Experience with data science lifecycle
Knowledge of applied statistics
Machine learning expertise
Artificial intelligence understanding
Analytical modeling capability