Salary for Senior-level / Expert Manager in Canada during 2024

Salary details

The average senior-level / expert Manager salary lies between USD 95,000 and USD 176,000 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: Jan. 19, 2025

Top 20 Job Tags for Senior-level / Expert Manager roles

The three most common job tag items assiciated with senior-level / expert Manager job listings are Engineering, Machine Learning and Python. 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:

Engineering | 3785 jobs Machine Learning | 2951 jobs Python | 2638 jobs Computer Science | 2362 jobs SQL | 2198 jobs Research | 1932 jobs Statistics | 1740 jobs Architecture | 1596 jobs Agile | 1465 jobs Security | 1372 jobs Testing | 1306 jobs Data management | 1236 jobs AWS | 1226 jobs R | 1219 jobs Data Analytics | 1200 jobs Privacy | 1131 jobs Mathematics | 1078 jobs Azure | 1040 jobs Data analysis | 984 jobs Pipelines | 930 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Manager job listings are Career development, Health care and Equity / stock options. 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 | 4369 jobs Health care | 2423 jobs Equity / stock options | 1711 jobs Flex hours | 1513 jobs Startup environment | 1505 jobs Competitive pay | 1379 jobs Salary bonus | 1269 jobs Team events | 1196 jobs Medical leave | 1050 jobs Insurance | 1023 jobs Flex vacation | 986 jobs Parental leave | 932 jobs Wellness | 596 jobs 401(k) matching | 595 jobs Transparency | 324 jobs Home office stipend | 263 jobs Relocation support | 222 jobs Flexible spending account | 207 jobs Conferences | 204 jobs Travel | 185 jobs

Salary Composition

In Canada, the salary composition for a Senior-level or Expert Manager in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10% to 20%. Additional remuneration, such as stock options, profit sharing, or other incentives, can make up the remaining 5% to 10%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Toronto or Vancouver might offer higher base salaries and more equity options compared to smaller cities. Similarly, larger companies or those in high-growth industries may provide more comprehensive bonus structures and stock options.

Increasing Salary Further

To increase your salary beyond the median level, consider pursuing roles with greater responsibility, such as Director or VP positions, which often come with higher compensation. Expanding your skill set to include emerging technologies or specialized areas within AI/ML can also make you more valuable. Networking within the industry and building a strong personal brand can open doors to higher-paying opportunities. Additionally, negotiating your salary based on market research and your proven track record can lead to better compensation packages. Seeking opportunities in high-demand sectors, such as finance or healthcare, where AI/ML expertise is particularly valued, can also result in higher salaries.

Educational Requirements

Most senior-level positions in AI/ML/Data Science require at least a master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Engineering. A Ph.D. can be advantageous, especially for roles that involve research or advanced technical leadership. Employers often look for candidates with a strong foundation in mathematics, programming, and data analysis, as well as experience in applying these skills to real-world problems.

Helpful Certificates

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty can be beneficial. These certifications validate your skills in specific tools and platforms commonly used in the industry. Additionally, completing courses from reputable institutions, such as those offered by Coursera, edX, or Udacity, can also be advantageous.

Required Experience

Typically, a senior-level position in AI/ML/Data Science requires at least 7 to 10 years of relevant experience. This includes hands-on experience in data analysis, machine learning model development, and project management. Experience leading teams and managing projects is crucial, as these roles often involve overseeing the work of other data scientists and collaborating with cross-functional teams. Demonstrated success in delivering impactful AI/ML solutions and a track record of innovation can set you apart from other candidates.

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