Data Scientist Salary in Canada during 2022

Salary details

The average Data Scientist salary lies between USD 67,597 and USD 100,000 in Canada. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Data Scientist roles

The three most common job tag items assiciated with Data Scientist job listings are Python, Machine Learning and SQL. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 2740 jobs Machine Learning | 2364 jobs SQL | 2008 jobs Statistics | 1994 jobs Engineering | 1885 jobs R | 1484 jobs Computer Science | 1477 jobs Research | 1436 jobs Mathematics | 1182 jobs Testing | 908 jobs ML models | 849 jobs PhD | 688 jobs Spark | 659 jobs AWS | 654 jobs Data analysis | 620 jobs NLP | 611 jobs Pipelines | 611 jobs Tableau | 604 jobs Economics | 589 jobs Deep Learning | 549 jobs

Top 20 Job Perks/Benefits for Data Scientist roles

The three most common job benefits and perks assiciated with Data Scientist job listings are Career development, Health care and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 2225 jobs Health care | 997 jobs Startup environment | 867 jobs Flex hours | 756 jobs Flex vacation | 660 jobs Team events | 608 jobs Equity / stock options | 566 jobs Parental leave | 519 jobs Competitive pay | 510 jobs Insurance | 474 jobs Salary bonus | 375 jobs Medical leave | 363 jobs Wellness | 349 jobs 401(k) matching | 281 jobs Home office stipend | 259 jobs Conferences | 215 jobs Unlimited paid time off | 170 jobs Fitness / gym | 156 jobs Snacks / Drinks | 96 jobs Gear | 95 jobs

Salary Composition

In Canada, the salary composition for a Data Scientist can vary significantly based on factors such as region, industry, and company size. Typically, the salary package includes a fixed base salary, which forms the bulk of the compensation. In addition to the base salary, many companies offer performance-based bonuses, which can range from 5% to 20% of the base salary, depending on the company's performance and the individual's contribution. Larger companies or those in high-demand industries like tech or finance may offer additional remuneration in the form of stock options, profit-sharing, or other incentives. In regions with a high cost of living, such as Toronto or Vancouver, salaries might be higher to compensate for living expenses.

Increasing Salary

To increase your salary as a Data Scientist, consider the following steps:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools such as deep learning, natural language processing, or cloud computing. Mastery of popular programming languages like Python and R, as well as proficiency in data visualization tools, can make you more valuable.

• Advanced Education: Pursuing a master's degree or a Ph.D. in a related field can open doors to higher-paying positions and leadership roles.

• Networking: Engage with professional communities, attend conferences, and participate in workshops to expand your network and learn about new opportunities.

• Industry Shift: Transitioning to industries that pay higher salaries for data science roles, such as finance, healthcare, or tech, can lead to a significant salary increase.

• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during job offers or performance reviews.

Educational Requirements

Most Data Scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. A strong educational background in quantitative fields is essential, as it provides the foundational knowledge needed to analyze and interpret complex data.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP): This certification validates your ability to transform data into valuable insights and is recognized across industries.

• Microsoft Certified: Azure Data Scientist Associate: This certification is beneficial if you work with Microsoft's Azure platform and want to demonstrate your skills in applying data science techniques.

• Google Professional Data Engineer: This certification is ideal for those working with Google Cloud Platform and focuses on designing, building, and operationalizing data processing systems.

Experience Requirements

Typically, entry-level Data Scientist roles require 1-3 years of experience in data analysis, machine learning, or a related field. For more senior positions, 5-10 years of experience is often expected. Experience can be gained through internships, co-op programs, or previous roles in data analysis or software development. Practical experience with data manipulation, statistical analysis, and machine learning models is crucial.

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