Salary for Senior-level / Expert Data Analyst in Canada during 2023

Salary details

The average senior-level / expert Data Analyst salary lies between USD 105,000 and USD 168,000 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: Oct. 28, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Analyst roles

The three most common job tag items assiciated with senior-level / expert 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 | 1947 jobs Python | 1386 jobs Tableau | 1187 jobs Statistics | 1121 jobs Data analysis | 950 jobs Engineering | 904 jobs R | 787 jobs Power BI | 756 jobs Excel | 740 jobs Data visualization | 678 jobs Data Analytics | 660 jobs Mathematics | 642 jobs Computer Science | 589 jobs Looker | 563 jobs Finance | 551 jobs Research | 494 jobs Business Intelligence | 494 jobs Machine Learning | 444 jobs KPIs | 443 jobs Testing | 442 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Analyst roles

The three most common job benefits and perks assiciated with senior-level / expert Data Analyst 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 2023 and the number of open jobs that where offering them during that period:

Career development | 1394 jobs Health care | 872 jobs Startup environment | 663 jobs Flex hours | 653 jobs Equity / stock options | 566 jobs Competitive pay | 536 jobs Flex vacation | 520 jobs Team events | 469 jobs Salary bonus | 437 jobs Insurance | 416 jobs Parental leave | 408 jobs Medical leave | 297 jobs 401(k) matching | 256 jobs Wellness | 227 jobs Home office stipend | 182 jobs Fitness / gym | 169 jobs Gear | 142 jobs Unlimited paid time off | 142 jobs Relocation support | 69 jobs Transparency | 61 jobs

Salary Composition

In Canada, the salary composition for a Senior-level or Expert Data Analyst in AI/ML/Data Science typically includes a mix of fixed salary, bonuses, and additional remuneration. The fixed salary is the base pay and usually constitutes the majority of the total compensation package. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, profit-sharing, or other incentives, which are more common in larger tech companies or startups. The composition can also vary by region, with tech hubs like Toronto and Vancouver offering higher salaries and more comprehensive packages compared to smaller cities.

Increasing Salary

To increase your salary further from this position, consider the following steps:

• Specialization: Develop expertise in a niche area within AI/ML, such as natural language processing, computer vision, or deep learning, which can command higher salaries.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Analytics, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML through courses, workshops, and conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during job offers or performance reviews.

Educational Requirements

Most Senior-level 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. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data modeling and machine learning tasks. Advanced degrees can provide a deeper understanding of theoretical concepts and practical applications, making candidates more competitive.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• Microsoft Certified: Azure Data Scientist Associate: Demonstrates proficiency in using Azure's machine learning tools.
• AWS Certified Machine Learning – Specialty: Validates expertise in building, training, and deploying machine learning models on AWS.

Required Experience

Typically, a Senior-level Data Analyst in AI/ML/Data Science is expected to have at least 5-8 years of relevant experience. This includes hands-on experience with data analysis, statistical modeling, and machine learning techniques. Experience in leading projects, mentoring junior analysts, and collaborating with cross-functional teams is also highly valued.

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