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

Salary details

The average senior-level / expert Data Manager salary lies between USD 113,000 and USD 180,000 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: Dec. 22, 2024

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

The three most common job tag items assiciated with senior-level / expert Data Manager job listings are Data management, Research and Testing. 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:

Data management | 285 jobs Research | 166 jobs Testing | 143 jobs Statistics | 131 jobs Excel | 125 jobs SAS | 111 jobs CDISC | 107 jobs Privacy | 101 jobs Data quality | 92 jobs Pharma | 78 jobs Engineering | 73 jobs SQL | 65 jobs Security | 65 jobs GCP | 57 jobs Data governance | 47 jobs Computer Science | 45 jobs Data analysis | 43 jobs R | 41 jobs Architecture | 34 jobs Consulting | 31 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Manager job listings are Career development, Team events and Health care. 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 | 200 jobs Team events | 120 jobs Health care | 118 jobs Flex hours | 78 jobs Insurance | 58 jobs Medical leave | 57 jobs Startup environment | 56 jobs Parental leave | 50 jobs Competitive pay | 49 jobs Salary bonus | 44 jobs Equity / stock options | 38 jobs Flex vacation | 38 jobs 401(k) matching | 26 jobs Wellness | 20 jobs Relocation support | 13 jobs Travel | 12 jobs Conferences | 11 jobs Gear | 10 jobs Home office stipend | 7 jobs Transparency | 6 jobs

Salary Composition for Senior-level/Expert Data Manager Roles

In Canada, the salary composition for a Senior-level or Expert Data Manager in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or benefits. 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 tied to company profits, usually account for 10% to 20%. Additional remuneration, such as stock options, profit-sharing, or other benefits, 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 companies in major cities like Toronto or Vancouver might offer higher base salaries and stock options, while smaller companies or those in less competitive regions might focus more on bonuses and benefits to attract talent.

Steps to Increase Salary from This Position

To increase your salary further from a Senior-level Data Manager position, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or AI ethics, which are in high demand and can command higher salaries.
• Pursue Leadership Roles: Transition into roles with greater managerial responsibilities, such as Director of Data Science or Chief Data Officer, which typically offer higher compensation.
• Expand Your Network: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities and salary trends.
• Negotiate Effectively: Leverage your experience and market research to negotiate better compensation packages during performance reviews or when switching jobs.

Educational Requirements

For a Senior-level or Expert Data Manager role, a strong educational background is essential. Most positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data analysis or research. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical methods, and data management techniques, which are crucial for this role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise to potential employers. Some valuable certifications include:

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

These certifications can validate your skills in data analysis, machine learning, and cloud-based data solutions, making you a more competitive candidate.

Required Experience

Typically, a Senior-level Data Manager position requires at least 5 to 10 years of experience in data science, analytics, or a related field. This experience should include a proven track record of managing data projects, leading teams, and delivering actionable insights from complex datasets. Experience in specific industries, such as finance, healthcare, or technology, can also be advantageous, as it provides domain-specific knowledge that can be critical for certain roles.

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