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One of the most rewarding and in-demand professions in the world is data science. It involves using data, algorithms, and technology to solve real-world problems and create value. Canada is one of the leading countries in data science and innovation, with a strong talent pool, a supportive ecosystem, and a diverse market. There are many opportunities for data scientists in Canada, from startups to multinational corporations, from public to private sectors, and research to development.
In this article, we have compiled a list of data scientist roles in Canada that you can explore and apply now. These roles are based on the latest job postings from various sources. Whether you are a beginner, intermediate, or advanced data scientist, you will find something that suits your skills, interests, and goals.
So, what are you waiting for? Check out the list below and start your data science journey in Canada today.
Location: Guelph, ON
Role: Lead Data Scientist
Qualification: Bachelor's/Master's degree in a related field
Required skills: 7+ years of progressive experience in data analysis/data science and handling of large data sets. Strong background in machine learning, predictive modeling, exploratory data analysis, and mathematical optimization techniques.
Responsibilities: Collaborate with teams in Taxonomy and Performance Marketing to proactively identify keyword trends & develop data-driven optimization strategies.
Location: Chalk River, ON
Role: Data Scientist
Qualification: Bachelor's and/or Master's degree in areas of Machine Learning, Computer Science, Applied Statistics or related field
Required skills: This includes intermediate or advanced programming skills in Python and machine learning libraries, such as TensorFlow, scikit-learn, PyTorch, etc. with experience analyzing real-world datasets.
Responsibilities: In collaboration with domain experts, develop new methods and technologies as an outcome of the research performed.
Location: Mississauga, ON
Role: Sr Manager Data Scientist
Qualification: Bachelors/Master's in engineering, Computer Science, Applied Mathematics, Operations Research, or related field, with a focus on Business Management
Required skills: Expert at data and model management. Extensive background in developing optimization and predictive models based on logic and machine learning. Strong in scalable data processing tools like Polars, Spark, and Pandas.
Responsibilities: Take the lead in integrating data science skills with practical business requirements to address real-world issues with quantifiable results.
Location: Montreal, Quebec, Canada
Role: Data Scientist
Qualification: Bachelor's/Master's degree in a related field
Required skills: Python, .net, C#, aerospace, aerospace engineering, physics, electrical engineering
Responsibilities: Provide methodical and implementation guidance as well as hands-on support around analytical use cases. Share insights with important stakeholders and promote the benefits of the use cases.
Location: Québec, QC
Role: Data Scientist – Machine Learning
Qualification: Bachelor's and/or Master's degree in areas of Machine Learning, Computer Science, Applied Statistics or related field
Required skills: A significant background in computer science, mathematics, statistics, artificial intelligence, and data science is preferred. Three years of minimum experience in data processing, model building, and machine learning pipeline construction for practical applications.
Responsibilities: Using cutting-edge programming tools and methodologies, do advanced research in machine intelligence and algorithm development.
Location: Montreal, QC
Role: Expert Data Scientist
Qualification: Master's degree or Ph.D. in Statistics, Quantitative Methods, Mathematics, or equivalent.
Required skills: Knowledge of polyglot databases (SQL, NoSQL, Graph, Search, Time-Series). Familiarity with data engineering (Databricks, Azure Data Factory).
Responsibilities: Apply your understanding of statistics and machine learning to particular business issues and data. Create programs that support the mechanical, logistics, and engineering teams in several extremely technical domains.
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