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Data science roles in Canada offer salaries between CAD 90 - 135K yearly.
Major hubs include Toronto, Vancouver, and Montreal, with growing demand.
Skills in Python, machine learning, and data visualization are essential.
Canada's data science sector is experiencing rapid growth, especially with an increasing demand for data-driven insights across various industries. The job market for data professionals is expanding swiftly, with opportunities available in diverse sectors, including finance, technology, and healthcare.
Both established companies and innovative startups require skilled data talent to leverage data analytics and inform business decisions. As a result, data science professionals in Canada have access to a wide range of career opportunities.
The sector's growth is expected to continue, driven by advancements in technology and the increasing importance of data-driven decision-making.
Below are the top 10 positions one is eligible to apply for in data science jobs in Canada.
A Data Scientist builds models, analyzes data, and identifies business problems. Data Scientists need several skills, including Python programming, a basic understanding of complex statistics, and the ability to input data and create visualisations.
Companies for these positions include banks, fintech startups, and retail. The workload is generally between 35 and 40 hours per week, the salary is comparable to other programming sectors, and is accompanied by benefits.
Lead Data Scientist is an ideal position for someone with experience in AI and domain knowledge in mining or geosciences. Employers will want candidates who can lead people and deploy models into production.
Knowledge of TensorFlow and cloud platforms would be expected. The combination of leadership (soft skills) as well as being a deep technical individual will be ideal for one’s employer.
The primary focus of this position is building and implementing machine learning models. A machine learning engineer in Canada must write clean code and integrate models into systems.
Strong programming skills are essential. Experience with frameworks such as Scikit-learn, TensorFlow, or PyTorch is a plus. These roles are typically found in tech product companies and financial institutions, including banks.
Also read: Top 10 Data Science Jobs to Apply in India
This role involves AI research and applying solutions in real-world systems. Companies expect a strong background in neural networks, deep learning, and cloud platforms. A PhD or years of industry expertise are frequently required.
It’s a good match for professionals looking to mix innovation with implementation.
The data analyst's role has specialist support teams with dashboards and insights. The job involves the use of Excel, SQL, Power BI, and occasionally Python.
While less technical than data science, it plays a vital support role. Companies seek candidates with attention to detail and strong communication skills.
This role focuses on user metrics and product growth. Data reporting, cohort analysis, and A/B testing are all included in the task. It’s a strategic role that connects business and data. Employers seek someone who understands both numbers and customer behavior.
Banks and insurance companies in Canada require data scientists for tasks such as credit scoring, fraud detection, and market analysis. These roles necessitate a combination of domain knowledge and data skills.
Tools used often include SQL, SAS, Python, and big data platforms. The financial sector values accuracy and risk management.
This is a niche role that combines geospatial data with data science. The job involves mapping, environmental modeling, and analysis. Tools such as ArcGIS and QGIS are utilized, along with Python, for automation purposes.
It's ideal for someone looking for analytics roles in Canada with both geography and analytics knowledge.
These positions require educational programs with real-world project work. Employers look for a variety of skills, such as data wrangling and basic modelling. There are many types of companies that offer internships, career development programs, and mentorship opportunities. So they are not a bad entry point into data science in Canada.
Internships are excellent for students or individuals without prior full-time work experience. Internship responsibilities include data cleaning, modeling small projects, and providing reports; internships often pay an hourly rate.
Internships could also lead to full-time offers—one of the better ways to break into the industry.
Data experts are in high demand in Canada across a wide range of industries and companies. If one is entering the data science field or looking for a new senior position, the demand is here, and more. With the right tools and approach, there is an opportunity for everyone to secure great data science jobs in Canada.
The moment to change careers is now.
