Salary for Senior-level / Expert Analyst in Canada during 2024
💰 The median Salary for Senior-level / Expert Analyst in Canada during 2024 is USD 86,462
✏️ This salary info is based on 24 individual salaries reported during 2024
Salary details
The average senior-level / expert Analyst salary lies between USD 73,000 and USD 115,200 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.
- Job title
- Analyst
- Experience
- Senior-level / Expert
- Region
- Canada
- Salary year
- 2024
- Sample size
- 24
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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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:Top 20 Job Tags for Senior-level / Expert Analyst roles
The three most common job tag items assiciated with senior-level / expert Analyst job listings are SQL, Python and Statistics. 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 | 5079 jobs Python | 4168 jobs Statistics | 3439 jobs Tableau | 3099 jobs Data analysis | 2848 jobs Engineering | 2823 jobs Excel | 2411 jobs Power BI | 2209 jobs R | 2152 jobs Research | 1910 jobs Data Analytics | 1910 jobs Computer Science | 1898 jobs Finance | 1836 jobs Data visualization | 1779 jobs Testing | 1772 jobs Mathematics | 1768 jobs Business Intelligence | 1533 jobs Data quality | 1491 jobs Machine Learning | 1453 jobs Economics | 1217 jobsTop 20 Job Perks/Benefits for Senior-level / Expert Analyst roles
The three most common job benefits and perks assiciated with senior-level / expert 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 | 4267 jobs Health care | 2903 jobs Flex hours | 1903 jobs Competitive pay | 1824 jobs Equity / stock options | 1583 jobs Startup environment | 1484 jobs Team events | 1379 jobs Insurance | 1376 jobs Flex vacation | 1242 jobs Medical leave | 1152 jobs Salary bonus | 1125 jobs Parental leave | 1088 jobs Wellness | 910 jobs 401(k) matching | 747 jobs Transparency | 354 jobs Fitness / gym | 279 jobs Home office stipend | 237 jobs Gear | 196 jobs Unlimited paid time off | 191 jobs Relocation support | 189 jobsSalary Composition
In Canada, the salary composition for a Senior-level or Expert Analyst in AI/ML/Data Science typically includes a mix of a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The fixed base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can make up 5-10% of the total package. Regional differences also play a role; for instance, salaries in major tech hubs like Toronto or Vancouver might be higher compared to other regions. 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 further from this position, consider the following strategies:
- Skill Enhancement: Continuously update and expand your skill set, particularly in emerging technologies and tools in AI/ML. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.
- Leadership Roles: Aim for leadership or managerial positions, which typically come with higher pay. This might involve leading a team of data scientists or managing large-scale projects.
- Networking: Build a strong professional network within the industry. Attend conferences, workshops, and seminars to connect with industry leaders and peers.
- Negotiation: When discussing salary, be prepared to negotiate. Research industry standards and be ready to present your achievements and contributions to justify a higher salary.
- Certifications and Education: Pursue advanced certifications or further education, such as a master's degree or Ph.D., which can enhance your qualifications and bargaining power.
Educational Requirements
Most senior-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, data science, statistics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for expert-level roles. These advanced degrees provide a deeper understanding of complex algorithms, data structures, and statistical methods, which are crucial for high-level analysis and decision-making.
Helpful Certifications
While not always mandatory, certain certifications can bolster your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:
- Certified Data Scientist (CDS)
- TensorFlow Developer Certificate
- AWS Certified Machine Learning – Specialty
- Microsoft Certified: Azure AI Engineer Associate
- Google Professional Machine Learning Engineer
These certifications can validate your skills in specific tools and platforms, making you more attractive to employers.
Required Experience
Typically, a senior-level position in AI/ML/Data Science requires at least 5-10 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in leading projects or teams is also highly valued, as it demonstrates your ability to manage complex tasks and collaborate effectively with others.
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