Data scientists in Canada in 2025 are earning an average salary of CAD 91,000 a year, with the highest amount going up to CAD 100,000 a year as well! Both of these figures are significantly higher than what is considered a good yearly salary in the country. They also demonstrate the excellent condition in which these professionals operate in the ever-evolving Canadian job market. The data-related job market in Canada is robust and growing, with opportunities in various sectors, including healthcare, online retail, finance, government, education, and technology.
This blog will discuss the top data science jobs in Canada, focusing on the salaries and the responsibilities that such professionals typically undertake as part of their work. It will also highlight the skills necessary to secure these jobs.
Source: Glassdoor
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Best Data Science Jobs in Canada – Salaries and Job Description
In 2025, the Canadian data science job market is experiencing significant growth, driven by advancements in areas such as artificial intelligence (AI), big data analytics, and machine learning. This surge is evident in various industries, including finance, e-commerce, healthcare, and technology.
| Job Designation | Average Salary |
| Data Engineer | CAD 140,810 |
| AI Engineer | CAD 135,439 |
| Machine Learning Engineer | CAD 100,000 |
| Data Scientist | CAD 91,000 |
| Data Analyst | CAD 67,000 |
Sources: Indeed and Glassdoor
Also Read: Why Data Science is One of the Most In-Demand Careers in Canada
Data Engineer
Data engineers are responsible for designing, maintaining, and building the data infrastructures of companies. Of all the different data science designations, they get the highest data science salary as well. They ensure that people who need timely and accurate data receive it, including data scientists, business users, and data analysts. They create the infrastructure to process and store data, such as databases, cloud-based storage solutions, and data warehouses.
AI Engineer
AI engineers design, implement, and develop AI applications and systems. They utilize their knowledge and skills in technologies such as machine learning, data analytics, and programming to create intelligent systems that can make decisions by learning from data. For this, they build AI models, deploy them in software solutions, and ensure that they function effectively even in larger applications. They utilize machine learning, model training, and deep learning techniques and tools to develop and refine AI models.
Machine Learning Engineer
Machine learning engineers utilize their data science skills and knowledge to design, implement, and develop machine learning algorithms that enable them to maintain and build AI systems capable of making predictions by learning from data. They work in data science teams with other members, such as deep learning engineers and data scientists, collaborating closely to create technical solutions for business problems. As part of their algorithm implementation and design work, these professionals select, implement, and design the most suitable algorithms for specific tasks, such as classification, clustering, and prediction.
Data Scientist
Data scientists collect, interpret, and analyze data to uncover insights and patterns, thereby enabling organizations and businesses to make informed decisions with more comprehensive information. They employ various techniques, including machine learning, data visualization, and statistical modeling, to identify trends, create actionable plans, and develop predictive models.
In their data preparation and collection work, they identify relevant data sources, gather information from both structured and unstructured formats, and then clean and transform the data to make it ready for analysis.
Also Read: How to Earn Passive Income as a Data Scientist in Canada?
Data Analyst
A data analyst is one of the leading data science jobs in Canada. These professionals collect, interpret, and clean data to help organizations understand trends, relationships, and patterns, thereby solving business problems and informing decision-making.
They employ various statistical tools and methods to analyze data, generate reports, and create visualizations, making their work more accessible and understandable for stakeholders. As part of their data preparation and collection work, these professionals gather data from various sources and ensure that it is relevant and accurate for analysis.
Top Data Science Jobs in Canada – Requisite Skills
The leading data analyst jobs in Canada require a combination of both technical and soft skills. Candidates must possess a high level of competence in both areas to have any chance of success, given the intense levels of competition in these profiles.
| Main Area | Requisite Skills |
| Technical Skills |
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| Soft Skills |
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Also Read: Python vs R for Data Science in Canada
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FAQs On Data Science Jobs in Canada
Q: What is the future of data science in Canada?
Ans: Data science has a promising future in Canada, with a growing demand for skilled professionals in the field and strong job prospects.
Q: What skills are essential for data scientists in the future?
Ans: In the future, data science professionals will need a combination of soft and technical skills, such as:
- Programming Languages
- Communication
- Machine Learning
- Critical Thinking
- Data Visualization
- Business Acumen
- Cloud Computing
Q: What educational background is needed for data science?
Ans: To work in a data science career, candidates would need a bachelor’s degree in a quantitative domain like computer science, statistics, or mathematics.
Q: Which industries are hiring data scientists in Canada?
Ans: The most prominent industries hiring data scientists in Canada are:
- Technology
- Financial Services
- Healthcare
- Retail/E-Commerce
- Government
- AI Agencies
Q: What certifications are valuable for data science jobs in Canada?
Ans: Data science certifications from industry leaders, as well as those that focus on specific technologies and platforms, are highly valued for securing data science jobs in Canada.
