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Home Singapore Blog Data Science & Analytics Top Industries Hiring Data Scientists in Canada

Top Industries Hiring Data Scientists in Canada

Tejaswi Singh by Tejaswi Singh
June 25, 2025
in Data Science & Analytics
Top Industries Hiring Data Scientists in Canada
OpenAI
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There are numerous companies hiring data scientists currently in Canada. The increasing adoption of AI, big data, and digital transformation initiatives in several industries is the main reason. The Government of Canada’s Job Bank forecasts demand for 29,300 data administrators and database analysts over the next decade. At the same time, data science jobs may grow by 36% from 2023 to 2033, according to reports.

If you want to land the best-paying data scientist jobs in Canada, knowing more about the top industries, employers, and market landscape is a must. This blog will acquaint you with the top companies hiring data scientists in Canada.

Take your skills to the next level — Explore Data Science Online Course

Top Industries Hiring Data Scientists in Canada

Here is a look at the leading industries and companies hiring data scientists in Canada.

IndustryAverage Salary (CAD per year)Top Recruiters
E-Commerce/Tech77,000-150,000Instacart, Shopify, Wealthsimple, Amazon, Google
Finance/Banking90,000-110,000Royal Bank of Canada (RBC), Desjardins, National Bank of Canada, CIC, Scotiabank, Morgan Stanley, Vanguard, Connor, Clark & Lunn Financial Group
Media/Legal60,000-140,000Clio, Thomson Reuters, RBC, TD, LegalShield, Google Canada, Shopify, Deloitte, EY, Accenture, Microsoft, Amazon
IT/Consulting77,000-158,107CGI, McKinsey, Deloitte, Fractal Analytics, Tiger Analytics, LatentView Analytics, Telus, and Rogers
Tech/Cloud60,000-140,000Amazon, Google, Shopify, Microsoft, IBM, Yellow.ai, Nvidia, Arya.AI, NIRMAI, Rephrase.ai, PwC, TD Bank, Deloitte
Public Sector60,000-120,000Federal Government of Canada, Government of Alberta, BC Government, Statistics Canada, HICC

E-Commerce/Tech

One of the most popular graduate jobs in data science is in the e-commerce sector. Key duties include analyzing customer behavior, optimizing digital or online marketing campaigns, and forecasting sales trends. Other tasks include creating customer recommendation systems, predictive models, and data visualization and reporting.

Finance/Banking

With an attractive salary package for data scientists, this industry is a favorable hunting ground for trained professionals. Your primary duties include creating and executing machine learning (ML) models for risk assessment, fraud detection, and customer analytics. You’ll also have to build models to forecast customer behavior, financial indicators, and market trends while communicating complex findings through concise visualizations.

Media/Legal

You will find several opportunities in the legal and media sectors with lucrative salaries. Some of your key tasks include data analysis, identifying trends, creating predictive models, and extracting data insights to support internal decision-making. You may also lead initiatives in data collection, preparation, modeling, visualization, and refinement, applying insights to contract assessment, legal analytics, and other areas.

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IT/Consulting

To succeed in this sector, you will need skills in data model development, programming tools, and visualization. Other duties may include creating ML models, generating insights, and leading data science projects. Strategic planning and data analysis are key, along with programming tools for data visualization and analysis.

Tech/Cloud

You can put your degree as a data scientist to good use in this industry, analyzing large datasets and generating insights for better business decisions and strategies. Other responsibilities may include model implementation and creation, data collection, strategic recommendations, and staying updated on the latest technologies and advancements in the field.

Public Sector

The Government of Canada and various other federal or state agencies hire data scientists in large numbers. You will need to create and execute multiple statistical models and machine learning (ML) algorithms while deploying predictive analytics to address public sector needs and challenges. Data mining and extraction skills are essential, as are problem-solving, data visualization, and effective communication. You may also be required to work on specific projects in healthcare, transportation, social services, and other related fields.

Also Read: Why Data Science is One of the Most In-Demand Careers in Canada

Data Science Industry Overview and Job Outlook

The data sector in Canada is booming thanks to the growing reliance on data to make decisions across every industry.  Digital transformation also plays a significant role in this context, as more companies are adopting technologies such as big data and artificial intelligence (AI). This has also created a high demand for data scientists. 

The demand for data scientists is exceptionally high across sectors such as technology, healthcare, finance, and government. 

The demand for core data science skills has been strong since 2018, and it is expected to continue to grow! 

The job market for data scientists in Canada is in rude health, with growth expected in multiple openings, especially for professionals with the right specialization and experience. It is expected that the job market for data scientists will grow by 36% over the 10 years from 2023 to 2033.  

Recruiters in Canada are actively seeking candidates proficient in programming languages such as R and Python, with database skills in Structured Query Language (SQL), and experts in machine learning (ML), cloud computing, and AI.

The following cities are expected to be regional hubs for data scientists in Canada:

  • Toronto
  • Vancouver
  • Montreal
  • Calgary
  • Ottawa 

Data science salaries in Canada vary based on region. For example, data scientists working in cities like Toronto receive higher salaries.

Source: upGrad, as of September 7, 2025

Top Canadian Companies Hiring Data Scientists 

The top data science recruiters in Canada are concentrated primarily in the electronic commerce (e-commerce), technology, finance and banking, and consulting sectors.  

The following table shows the top companies in Canada hiring data scientists:

Sector Companies
E-Commerce and Technology 
  • Google 

  • Microsoft

  • Systems, Applications & Products in Data Processing (SAP)

  • Amazon

  • Shopify

  • Instacart  
Banking and Finance 
  • Royal Bank of Canada (RBC)

  • Bank of Montreal (BMO) Financial Group

  • Toronto-Dominion (TD) Bank

  • Scotiabank 
Consulting and Other Industries 
  • Deloitte 

  • Capgemini

  • Ernst & Young (EY)

  • Clio

Source: upGrad, as of August 26th, 2025; and Glassdoor, as of October 6, 2025

Career Roadmap: How to Enter Data Science

The first step that you need to take in this regard is to obtain a relevant degree. The standard requirement in these cases is a bachelor’s degree in subjects like computer science, mathematics, or statistics. Many employers also look for candidates with a doctor of philosophy (PhD) or a master’s degree in such subjects. 

You need to keep certain other factors in mind to stand a good chance of working in Canada’s data science industry:

Broader Point Specific Factors 
Getting the right skills and education. 
  • Acquiring key technical skills.
  • Gaining practical experience.
  • Considering certifications. 
Building a professional profile. 
  • Creating a strong portfolio.
  • Crafting a targeted cover letter and resume.
  • Preparing for interviews.
Finding opportunities and networking. 
  • Networking strategically.
  • Looking for entry-level roles.
  • Considering internships.
Understanding Canadian requirements. 
  • Work permit.
  • Language proficiency. 

Skills & Tools Needed to Get Hired as a Data Scientist

Canadian companies hiring data scientists require key skills and knowledge of specific tools when filtering applicants. They include:

  • Knowledge/certification in Python, SQL, and R, along with Tableau and AWS.
  • Statistical and mathematical foundation.
  • Machine learning knowledge, including decision trees, random forests, linear regression, and neural networks.
  • Data manipulation, cleaning, wrangling, preprocessing, and analysis skills.
  • Data visualization with tools like Seaborn, Matplotlib, Power BI, or Tableau.
  • Communication, analytical problem-solving, and collaborative skills.

Also Read: Data Science vs. AI vs. Machine Learning: Which Career Path is Best for You in Canada?

Future Outlook: AI and Emerging Sectors 

The key current trends in data science in Canada are:

  • Integration of ML and AI 
  • Focus on Responsible and Explainable AI (XAI)
  • Growth of Specialized Roles 
  • Focus on Real-Time Edge and Data Analytics 
  • Climate and Sustainability Innovation

The key challenges facing the data science industry in Canada are talent shortage, brain drain, and an adoption gap.

The most prominent industries driving the growth of data science in Canada are:

  • Finance 
  • Healthcare 
  • E-Commerce and Technology 
  • Public Sector 
  • Natural Resources and Manufacturing 

Apart from these, you still need considerable technical and soft skills, along with specialized knowledge, to make it big in Canada’s data science industry. 

How upGrad Can Help You Land a Data Science Role in Canada

Find industry-leading data science programs that help you land your dream job in Canada, courtesy of upGrad. You can expect cutting-edge courses with a Generative AI-integrated curriculum, real-world case studies and projects, and the latest data science and ML languages and tools. Other perks include career support, mentorship, and partnerships with leading global universities.

Completing your course from upGrad will go a long way in helping you achieve your dream career goals in Canada. You can consider these courses to start your learning journey:

  • Executive Diploma in Data Science and AI with IIIT-B
  • Master of Science in Data Science from Liverpool John Moores University

Must read articles:

  • Top Companies Hiring Data Scientists in Canada
  • Top 10 Online Data Science Courses & Certifications in Canada for 2026
  • Top Data Science Skills You’ll Learn in a Course — And Why They Matter
  • Want to Be a Data Scientist in Canada?
  • Best Universities for Pursuing a Data Science Course in Canada
  • Data Science vs. AI vs. Machine Learning
  • Canada’s Highest Paying Non-Tech Roles in 2026

🎓 Explore Our Top-Rated Courses in Canada

Take the next step in your career with industry-relevant online courses designed for working professionals in Canada.

  • DBA Courses in Canada
  • Data Science Courses in Canada
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  • Master of Education Courses in Canada
  • AI ML Courses in Canada
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View All Courses

FAQs on Top Companies Hiring Data Scientists in Canada

Which companies are hiring data scientists in Canada right now? 

Several companies in Canada are currently hiring data scientists, such as:

1. DoorDash
2. Telus
3. Lyft
4. Instacart
5. TD Bank
6. RBC
7. Rakuten Kobo

What is the average salary of a data scientist in Canada? 

The average salary of a data scientist in Canada is approximately CAD 97,258 annually. Salaries vary from CAD 84,950 to CAD 129,891, depending on the location, experience, and many other factors.

What qualifications do I need to get hired as a data scientist? 

You will need an educational background in mathematics, statistics, computer science, or related disciplines. Another requirement is strong communication skills, a portfolio of projects or practical experience, and certifications in data modeling, analytics, machine learning, and other relevant fields.

What entry-level data science roles are available in Canada? 

Some entry-level positions for data science in Canada include Junior Data Scientist, Data Visualization Specialist, Data Analyst, Machine Learning Engineer, and Junior Data Engineer. It varies from one industry to another.

Can I switch to data science from a non-tech background? 

Yes, you can switch to data science from a non-technical background. Of course, a robust technical foundation and mathematical or statistical knowledge are beneficial, but not mandatory. Many professionals have successfully switched to data science from diverse backgrounds like business, marketing, arts, and more.

Tejaswi Singh

Tejaswi Singh

3 articles published

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