Salary for Mid-level / Intermediate Data Specialist in Canada during 2024

Salary details

The average mid-level / intermediate Data Specialist salary lies between USD 83,150 and USD 118,000 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: Nov. 17, 2024

Top 20 Job Tags for Mid-level / Intermediate Data Specialist roles

The three most common job tag items assiciated with mid-level / intermediate Data Specialist job listings are Excel, Data management and Data quality. 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:

Excel | 236 jobs Data management | 179 jobs Data quality | 174 jobs Research | 146 jobs SQL | 108 jobs Privacy | 107 jobs Data analysis | 102 jobs Engineering | 100 jobs Testing | 97 jobs Finance | 93 jobs Security | 83 jobs Power BI | 79 jobs Data visualization | 73 jobs GCP | 56 jobs Pharma | 56 jobs Python | 54 jobs SAS | 54 jobs Data governance | 54 jobs Tableau | 49 jobs Statistics | 46 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Specialist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Specialist 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 | 223 jobs Health care | 155 jobs Flex hours | 142 jobs Competitive pay | 91 jobs Team events | 85 jobs Startup environment | 78 jobs Equity / stock options | 69 jobs Flex vacation | 68 jobs Insurance | 67 jobs Salary bonus | 54 jobs Medical leave | 44 jobs Parental leave | 42 jobs Wellness | 40 jobs 401(k) matching | 26 jobs Relocation support | 16 jobs Home office stipend | 14 jobs Gear | 12 jobs Transparency | 12 jobs Conferences | 12 jobs Flexible spending account | 8 jobs

Salary Composition

In Canada, the salary composition for a mid-level/intermediate data specialist in AI/ML/Data Science typically includes a fixed base salary, performance bonuses, and additional remuneration such as stock options or benefits. The fixed base salary is the largest component, often constituting 70-85% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 5-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5-15%.

The composition can vary by region, with tech hubs like Toronto and Vancouver offering higher base salaries and more lucrative stock options due to the competitive job market. Industry also plays a role; for instance, tech companies might offer more stock options, while financial institutions might provide higher bonuses. Larger companies often have more structured bonus programs and benefits, whereas startups might offer more equity.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously upgrade your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, and big data technologies.
• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends.
• Leadership Roles: Aim for roles that offer leadership responsibilities, such as team lead or project manager, which often come with higher pay.
• Industry Switch: Consider moving to industries that pay higher salaries for data specialists, such as finance or healthcare.

Educational Requirements

Most mid-level data specialist roles require at least a bachelor's degree in a relevant field such as computer science, data science, statistics, or engineering. A master's degree can be advantageous and is sometimes preferred, especially for roles that require more advanced analytical skills or leadership responsibilities.

Helpful Certifications

Certifications can enhance your profile and demonstrate expertise in specific areas. Some valuable certifications include:

• Certified Data Scientist (CDS)
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level data specialist role requires 3-5 years of experience in data analysis, machine learning, or a related field. Experience with data visualization tools, statistical analysis, and programming languages like Python or R is often necessary. Experience in managing projects or leading small teams can also be beneficial.

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