Salary for Mid-level / Intermediate Data Analyst in Canada during 2024

Salary details

The average mid-level / intermediate Data Analyst salary lies between USD 68,561 and USD 110,000 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. 24, 2024

Top 20 Job Tags for Mid-level / Intermediate Data Analyst roles

The three most common job tag items assiciated with mid-level / intermediate Data Analyst job listings are SQL, Python and Data analysis. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

SQL | 1656 jobs Python | 1145 jobs Data analysis | 1136 jobs Statistics | 1072 jobs Excel | 1004 jobs Tableau | 969 jobs Power BI | 869 jobs Engineering | 814 jobs Computer Science | 707 jobs Data visualization | 654 jobs Data Analytics | 616 jobs Research | 574 jobs R | 573 jobs Mathematics | 567 jobs Finance | 490 jobs Data quality | 429 jobs Testing | 393 jobs Business Intelligence | 383 jobs Economics | 370 jobs KPIs | 343 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Analyst roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 2024 and the number of open jobs that where offering them during that period:

Career development | 1274 jobs Health care | 894 jobs Flex hours | 620 jobs Competitive pay | 522 jobs Startup environment | 436 jobs Equity / stock options | 424 jobs Insurance | 408 jobs Team events | 386 jobs Flex vacation | 378 jobs Salary bonus | 352 jobs Parental leave | 327 jobs Medical leave | 317 jobs Wellness | 262 jobs 401(k) matching | 247 jobs Home office stipend | 89 jobs Flexible spending account | 78 jobs Fitness / gym | 77 jobs Unlimited paid time off | 76 jobs Transparency | 75 jobs Gear | 71 jobs

Salary Composition

In Canada, the salary composition for a Mid-level/Intermediate Data Analyst in AI/ML/Data Science typically includes a fixed base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The fixed base salary is the largest component, often accounting for 70-85% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 5-20% of the base salary. Additional remuneration, such as stock options, is more common in tech companies or startups and can add another 5-10% to the total compensation. Regional differences also play a role; for instance, salaries in major tech hubs like Toronto or Vancouver might be higher compared to smaller cities. Similarly, larger companies or those in high-demand industries like finance or technology may offer more competitive compensation packages.

Increasing Salary

To increase your salary from a Mid-level Data Analyst position, consider the following strategies:

• Skill Enhancement: Acquire advanced skills in machine learning, deep learning, or big data technologies. Proficiency in tools like TensorFlow, PyTorch, or Apache Spark can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or AI can open up higher-paying roles.
• Networking: Engage with professional networks and attend industry conferences to learn about new opportunities and trends.
• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.
• Industry Shift: Consider moving to industries that pay more for data expertise, such as finance, healthcare, or tech.

Educational Requirements

Most mid-level data analyst positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree in data science, analytics, or a related field is increasingly preferred, especially for roles that involve more complex data modeling and machine learning tasks. Some positions may also value interdisciplinary degrees that combine business and technical skills.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• SAS Certified Data Scientist

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

Required Experience

Typically, a mid-level data analyst role requires 3-5 years of experience in data analysis or a related field. This experience should include hands-on work with data manipulation, statistical analysis, and data visualization tools. Experience with programming languages such as Python or R, as well as familiarity with SQL databases, is often essential. Additionally, experience in a specific industry can be advantageous, as it provides context and understanding of industry-specific data challenges.

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