Turn piles of data into predictions and decisions. Math, code and a lot of cleaning up.
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Pay, the path, pros and cons and the facts on one printable page. Good for a wall or a guidance counsellor.
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What you earn and what it costs to get there.
Typical
$96,000
Junior
$62,000
Senior or lead
$145,000
Job Bank's national median is $46.15 an hour, about $96,000 a year full time. Job Bank pools this title with the wider data scientists group (NOC, the National Occupational Classification, code 21211), which also covers machine learning engineers. Big banks and tech companies in Toronto pay above this. Government and small companies pay below.
$60,000 to $75,000
Junior data scientist or data analyst moving up
Job Bank's low end is $30 an hour. Many first jobs are titled data analyst. A master's degree usually starts a step higher than a bachelor's.
$120,000 to $145,000+
Senior data scientist, lead, or manager of a data team
Job Bank's top end is $69.74 an hour. Stock and bonuses at large tech companies push total pay past this. Specialists in machine learning tend to earn the most.
Tuition, fees, exams and kit. Not rent, food or travel
The low end is someone already working with data, often as an analyst, who teaches themselves statistics and programming with free open source tools and moves across into the job. A few paid online courses is the whole bill. The high end is a four year bachelor's degree plus the master's degree that about half of job ads ask for, both priced at the top of their ranges. The cheap door is genuinely hard: most postings still filter on a degree, so you need to already be inside a company that can see your work. A stranger applying from outside with no credential is usually screened out before anyone opens the portfolio.
About half of job ads want a master's degree. Co-op terms in a data science degree pay well and often lead to the first job.
Remote or hybrid work
Normal, though banks want some office days.
Stock options or RSUs (restricted stock units, company shares you receive over time)
At tech companies.
Conference and learning budgets
The field moves fast and employers pay to keep you current.
Pension
If you work for Statistics Canada, a province or a bank.
The exact path from high school to qualified.
Math first, code second, then a lot of practice on real messy data.
High school
Grades 11 and 12
Take every math course: Advanced Functions, Calculus and Vectors, Data Management if your province offers it. Computer science helps.
Bachelor's degree
4 to 5 years with co-op
Data science (Waterloo, UBC, Simon Fraser, Toronto and many others now offer it), statistics, math or computer science. Choose co-op. Waterloo admits data science at averages in the mid-80s.
Projects and co-op
During school
Kaggle competitions, a public GitHub, and paid co-op terms at banks, Shopify, Statistics Canada or startups.
Master's degree (common, not required)
1 to 2 years
A 1 to 2 year master's in data science, statistics or computer science. Many jobs ask for it.
First job
After graduation
Often as a data analyst or junior data scientist, then promoted once you have shipped a model that made the company money.
Advanced Functions and Calculus
Required for every route in.
Data Management or statistics
The heart of the job.
Computer science
Python is the daily tool.
English
You will explain results to people who do not do math. That is half the job.
No licence, no exam, no professional body. The Statistical Society of Canada offers voluntary accreditation for statisticians, but almost no data science job asks for it. Employers judge you on your degree, your portfolio and a technical interview. Engineers Canada lists data scientist as an acceptable title for unlicensed people, unlike anything with engineer in it.
Things you don't need, but that help.
Machine learning in production
Building models that run inside real products, not just in notebooks. This is the bridge to machine learning engineer pay.
Cloud data platforms
AWS (Amazon Web Services), Azure or Google Cloud certificates. Banks want them.
SQL (the language for querying databases) at an expert level
Unglamorous, and the skill most junior data scientists are weakest at.
A domain
Finance, health, retail or insurance. Knowing the business doubles your value.
Kaggle or public projects
A model on real data, explained clearly, is your portfolio.
A master's degree
Not required, but it clears the filter on many job ads.
Presentation skills
Data scientists who can present get promoted. The rest stay in the notebook.
Canada punches above its weight in AI research. The Vector Institute in Toronto, Mila in Montreal and Amii in Edmonton fund scholarships, internships and labs for graduate students. A PhD path through one of them leads to research scientist jobs at Google, Microsoft or a Canadian lab, at pay well above a typical data scientist.
Day to day, pros and cons, where you'd work.
A meeting with a business team about a question: which customers will leave next month, or why sales dropped in Alberta. Then hours pulling data with SQL (the language for querying databases), cleaning it, and trying models in Python. Most of the time goes to the cleaning, not the modelling. Late in the day, a chart and a short write-up for people who will never look at your code. Some days you present, and those are the days that matter for your career.
The good
The hard parts
Things people don't tell you.
In 2017 Canada became the first country with a national AI strategy, putting $125 million into research through three institutes: Vector in Toronto, Mila in Montreal and Amii in Edmonton. A second phase added hundreds of millions more.
The federal statistics agency in Ottawa runs the census and hundreds of surveys, and hires statisticians and data scientists straight out of university, with a pension. It is one of the few places where the data is about the whole country.
Geoffrey Hinton, a University of Toronto professor, shared the 2024 Nobel Prize in Physics for the neural network research that underpins modern AI. Much of that work was done in Toronto with government research funding.
Data scientists regularly report that the majority of their time goes to finding, cleaning and organizing data. The model is often the quickest part. People who enjoy tidying up do well here.
Last checked September 2026. Pay figures are typical full-time annual amounts in Canadian dollars, based on Government of Canada Job Bank wage data and published salary grids. They vary by province, employer and experience. Tuition is for domestic students.