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 199,700 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. 10, 2024

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 | 3141 jobs Machine Learning | 2435 jobs Python | 2188 jobs Computer Science | 1985 jobs SQL | 1832 jobs Research | 1632 jobs Statistics | 1442 jobs Architecture | 1311 jobs Agile | 1245 jobs Security | 1127 jobs Testing | 1080 jobs AWS | 1041 jobs Data management | 1034 jobs R | 1022 jobs Data Analytics | 991 jobs Privacy | 940 jobs Mathematics | 912 jobs Azure | 836 jobs Data analysis | 820 jobs Finance | 778 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 | 3644 jobs Health care | 2067 jobs Equity / stock options | 1444 jobs Flex hours | 1290 jobs Startup environment | 1258 jobs Competitive pay | 1188 jobs Salary bonus | 1061 jobs Team events | 1029 jobs Medical leave | 881 jobs Insurance | 874 jobs Flex vacation | 849 jobs Parental leave | 786 jobs Wellness | 529 jobs 401(k) matching | 515 jobs Transparency | 257 jobs Home office stipend | 217 jobs Flexible spending account | 181 jobs Relocation support | 178 jobs Conferences | 175 jobs Fitness / gym | 171 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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