Data Analyst Salary in Canada during 2023

Salary details

The average Data Analyst salary lies between USD 95,000 and USD 149,200 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. 24, 2024

Salary trend

Top 20 Job Tags for Data Analyst roles

The three most common job tag items assiciated with Data Analyst job listings are SQL, Python and Tableau. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

SQL | 3888 jobs Python | 2788 jobs Tableau | 2263 jobs Statistics | 2193 jobs Data analysis | 2095 jobs Excel | 1956 jobs Engineering | 1771 jobs Power BI | 1732 jobs R | 1469 jobs Mathematics | 1350 jobs Data Analytics | 1309 jobs Data visualization | 1264 jobs Computer Science | 1255 jobs Research | 1138 jobs Finance | 1100 jobs Business Intelligence | 977 jobs Looker | 863 jobs KPIs | 844 jobs Testing | 843 jobs Machine Learning | 825 jobs

Top 20 Job Perks/Benefits for Data Analyst roles

The three most common job benefits and perks assiciated with Data Analyst job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 2882 jobs Health care | 1761 jobs Flex hours | 1418 jobs Startup environment | 1378 jobs Team events | 1086 jobs Competitive pay | 1071 jobs Flex vacation | 1024 jobs Equity / stock options | 913 jobs Insurance | 845 jobs Salary bonus | 824 jobs Parental leave | 744 jobs Medical leave | 536 jobs 401(k) matching | 456 jobs Wellness | 390 jobs Home office stipend | 300 jobs Fitness / gym | 295 jobs Gear | 262 jobs Unlimited paid time off | 228 jobs Relocation support | 157 jobs Yoga | 128 jobs

Salary Composition

In Canada, the salary composition for a Data Analyst in AI/ML/Data Science typically includes a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The fixed base salary is the most significant component, often accounting for 70-80% of the total compensation package. Performance bonuses can vary widely, ranging from 10-20% of the base salary, depending on the company's performance and individual achievements. Additional remuneration, such as stock options or profit-sharing, is more common in larger tech companies or startups and can significantly enhance total compensation, especially in high-growth industries or regions like Toronto or Vancouver.

Increasing Salary

To increase your salary from a Data Analyst position, consider pursuing advanced roles such as Data Scientist, Machine Learning Engineer, or Data Science Manager. These roles typically offer higher compensation due to increased responsibilities and required expertise. Enhancing your technical skills in programming languages like Python or R, gaining proficiency in machine learning frameworks, and developing strong data visualization skills can make you more competitive. Additionally, pursuing further education, such as a master's degree in data science or a related field, or obtaining relevant certifications, can also lead to salary growth. Networking within the industry and seeking opportunities in high-demand sectors like finance, healthcare, or technology can also be beneficial.

Educational Requirements

Most Data Analyst positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. Some employers may prefer candidates with a master's degree, especially for more advanced roles. A strong foundation in statistical analysis, data manipulation, and programming is essential. Coursework or experience in machine learning, data mining, and big data technologies can also be advantageous.

Helpful Certifications

Several certifications can enhance your qualifications and make you more attractive to employers. Some popular certifications include:

• Certified Analytics Professional (CAP): This certification demonstrates your ability to transform data into valuable insights.
• Microsoft Certified: Azure Data Scientist Associate: Focuses on using Azure's machine learning tools.
• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.
• IBM Data Science Professional Certificate: Offers a comprehensive introduction to data science and machine learning.

These certifications can help you stand out in a competitive job market and may lead to higher salary offers.

Required Experience

Typically, employers look for candidates with 2-5 years of experience in data analysis or a related field. Experience with data visualization tools (such as Tableau or Power BI), statistical software (like SAS or SPSS), and programming languages (such as Python or R) is often required. Experience in specific industries, such as finance, healthcare, or technology, can also be beneficial, as it provides context for data-driven decision-making within those sectors.

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