Salary for Mid-level / Intermediate Data Scientist in Canada during 2023

Salary details

The average mid-level / intermediate Data Scientist salary lies between USD 82,254 and USD 125,000 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

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate Data Scientist job listings are Python, Machine Learning and Statistics. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Python | 599 jobs Machine Learning | 539 jobs Statistics | 464 jobs SQL | 410 jobs Engineering | 372 jobs Computer Science | 325 jobs R | 314 jobs Research | 297 jobs Mathematics | 251 jobs Data analysis | 191 jobs ML models | 179 jobs Testing | 144 jobs Data visualization | 144 jobs AWS | 143 jobs Tableau | 131 jobs Data Mining | 131 jobs NLP | 129 jobs Deep Learning | 124 jobs TensorFlow | 120 jobs Scikit-learn | 116 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Scientist 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 2023 and the number of open jobs that where offering them during that period:

Career development | 524 jobs Health care | 249 jobs Flex hours | 176 jobs Competitive pay | 168 jobs Startup environment | 165 jobs Team events | 150 jobs Equity / stock options | 110 jobs Flex vacation | 110 jobs Parental leave | 103 jobs Insurance | 99 jobs Salary bonus | 83 jobs Medical leave | 81 jobs Conferences | 73 jobs 401(k) matching | 61 jobs Fitness / gym | 48 jobs Wellness | 39 jobs Unlimited paid time off | 37 jobs Home office stipend | 30 jobs Gear | 26 jobs Yoga | 23 jobs

Salary Composition

In Canada, the salary composition for a mid-level data scientist typically includes a fixed base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The base salary is the largest component and can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Toronto or Vancouver might offer higher base salaries compared to smaller cities. Industries such as finance or tech often provide more competitive compensation packages, including substantial bonuses and stock options, compared to sectors like healthcare or education. Larger companies may also offer more comprehensive benefits and additional perks, such as professional development funds or wellness programs.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, or big data technologies.
• Advanced Education: Pursuing a master's degree or a Ph.D. in a relevant field can open doors to higher-paying roles.
• Networking: Engage with professional networks and communities to learn about new opportunities and industry trends.
• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.
• Industry Switch: Transitioning to a higher-paying industry, such as finance or tech, can also lead to a salary increase.

Educational Requirements

Most mid-level data scientist positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree or even a Ph.D., especially for roles that involve complex data analysis or research. A strong educational background provides a solid foundation in the theoretical and practical aspects of data science.

Helpful Certifications

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

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

These certifications can validate your skills in specific tools and platforms, making you a more attractive candidate.

Experience Requirements

Typically, a mid-level data scientist is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and data visualization. Experience in handling real-world data problems, collaborating with cross-functional teams, and deploying models into production is highly valued.

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