Canadian universities have some of the best master’s degree programs in Data Science and Analytics. A career in Data Science is one of the most promising professional categories with some of the best salaries in the Canadian employment landscape. Data scientists and data analytics experts earn well even at the early stages of employment. A data scientist’s job in Canada cannot be uninteresting because of the growing need to address massive loads of unprocessed data in companies.
A data scientist’s average income in Canada is higher than in most other countries. The demand and versatility of a data science degree provide students with diverse work opportunities. Per Glassdoor, the average salary of a Data Scientist in Canada is CAD 98,941 per year or CAD 49.08 per hour. The starting data scientist salary in Canada is CAD 77,000 annually, with most experienced individuals earning up to CAD 137,000 annually. Students must learn the skills considering the scope of data science in Canada.
In-Demand Skills for Top-Tier Data Science Jobs
Data science is a high-end employment option. Students with significant abilities get jobs in top-tier positions in businesses. The more skillsets an expert has, the more successful they are. Regardless of function or duties, students must be adept in the following:
1. Mathematics and Statistics
Data scientists must be able to perform mathematical and statistical calculations. These are intertwined and demand efficiency. Data-driven companies hire data scientists to research and determine various statistical approaches, such as tests, processes, estimators, and distributors. The outcomes are critical for crucial business decisions. Data scientists should have a working knowledge of calculus and mathematics to gain expertise in machine learning. The requirement of statistics shouldn’t be surprising.
2. Programming
The most crucial aspect of Data Science is programming. A data scientist cannot sustain or do justice to the job profile without proficiency in computer languages. Professionals with programming knowledge and expertise are paid the highest in the Canadian job market. Java, Python, Hadoop, SQL, and C++ are just a few of the programming languages one should master.
3. Data Communication and Visualization
Data communication and visualization are essential aspects of data analysis. Unstructured data is complex to work with. So, it is essential to represent and organize data simply and visually understandable. This is important because the marketing decisions of many businesses are entirely data-driven. It depends on how well the data is interpreted. Multiple tools, like Tableau and Power Business Intelligence, help data scientists master data communication.
Software engineering expertise and abilities come in handy while dealing with massive quantities of data. Data scientists with software engineering skills are in high demand, and employers are willing to pay extra for them.
5. Data Analytics and Remodeling
The quality of insights depends on the data scientists. The data scientist’s skills in modeling and analytics are highly expected. Communication, analysis, and critical thinking will play a vital role in modeling data. Data scientists need to run tests, process and analyze data, and create various models to understand and predict outcomes.
6. Communication
Data is meaningless unless it is communicated. Individuals looking for a data scientist position in a company should have strong communication skills. It might be as simple as explaining how to get from point A to point B or discussing data visualization approaches, and presenting business growth forecasts & marketing statistics.
Data is extracted from a variety of sources, such as MySQL, Google Analytics, and MongoDB. The more sources used, the higher the data quality. To examine this unstructured data, it is put into the right structure or format. The data must be stored in a data warehouse after analysis. The data scientists interpret the information in this section. Data science applicants with experience in extracting, transforming, and importing data have a bright future.
8. Intellectual Thinking
Data scientists must use their intellect to think outside the box and decipher the correct meaning. They should be able to solve issues and examine solutions with intellect. To understand and interpret data in numerous ways, a data scientist must be curious, too.
9. Machine Learning and Deep Learning
Machine learning is the process of making devices and gadgets smart enough to decide and think independently. To avoid losses, data scientists must be well-versed in algorithms and be able to generate profitable forecasts. Deep learning is a concept that involves using neural networks to learn. For machine learning experts, Python is the most significant programming language. TensorFlow is a well-known Python library for building deep learning models.
Top Data Scientist Recruiters in Canada (For 2024)
The Canadian job market has a wide range of multinational companies and organizations. Employers from various sectors, like banking, information technology, healthcare, retail, and services, hire data science professionals at good pay packages. Here are some of the leading industries in the Canadian job market for data science jobs:
Top Data Science Job Opportunities in Canada (For 2024)
Job Title
Job Description
Average Annual Salary (CAD)
Senior Data Scientist
Senior Data Scientist is one of the high-end and top positions after an MS degree in Data Science.
$1,35,351
Business Intelligence Analyst
BI analysts use data to help organizations make sound business decisions. They are hired by top companies to program tools and build data models to visualize.
$72501
Data Architect
Data Architect is a management discipline concerned with designing, creating, deploying, and managing an organization’s data architecture.
$1,20,026
Business Intelligence Developer
BI developer is an engineer who uses business intelligence software to interpret and display data for an organization. Individuals with data science and software engineering skills can take up this role.
$88,658
Application Architect
Applications architecture describes the behaviour of applications used in a business, focusing on how they interact with each other and with users. It is highly in demand in the gaming and information technology industries.
$105,319
Big Data Engineer
Big data behavior engineers are the top-ranked career opportunities after Data Science. Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data useful.
$1,06,992
Business Analyst
A business analyst is a popular career and individuals need to have good communication skills, programming knowledge, and know-how to make business decisions quickly.
$68,883
Data Scientist
Data scientists are responsible for collecting, analyzing, and interpreting the large amounts of data available for data-driven businesses.
$98,941
Machine Learning Scientist
Machine learning scientists work with data and build machine learning models to help devices make the right decisions.
$129,325
Data Analyst
A data analyst is one of the most popular job opportunities after an MS in Data Science. The opportunities are ample since various sectors in the Canadian job market hire data analysts regularly.
$72,025
Data Mining Engineer
Data mining engineers are in high demand. They are responsible for designing and interpreting data for high-traffic transactional systems. It is a great job opportunity after taking a data science course in Canada.
$105,006
Machine Learning Engineer
A machine learning engineer is a second-best opportunity after a Machine Learning Scientist. Data-driven businesses are flourishing in Canada. Hence, the need for Machine Learning engineers is huge. Good knowledge of programming languages, communication, data modeling, and analytics skills will be essential for a good salary package.
A data scientist must learn some crucial programming languages along with statistical computations. They need to master strong communication and interpersonal skills.
The essential technical skills include:
Python programming
R programing
Hadoop platform
SQL databases
Machine learning and AI
Data visualization
Business strategy
Apart from this, the interpersonal skills include: Good communication Storytelling ability for statistical computations Ability to collaborate with various teams of an organization Learning new concepts
Data scientist salaries in Canada and the rest of the world are comparatively lower than machine learning engineers. Both machine learning and data science are interdependent. Machines cannot understand anything without data, and data science goes well with machine learning; they are usually regarded as complementary domains. The average data scientist salary in Canada is CAD 107,500, while that for machine learning scientists is CAD 162,625.
Pay by Experience Level for Data Scientists
If you have a master’s in data science, the salary keeps increasing impressively, which is as high as CAD 199,000 approximately for freshers, and for PhD holders, it is CAD 273,000. In contrast, a bachelor’s degree can get you CAD 149,000.
Here is an approximate salary chart for data scientists according to the level of work:
A data scientist’s average annual salary in Canada is around 95,700 CAD (Rs 55 lakh). It is more than the average salary in any other country. Canada is a global leader in education, with some of the world’s best colleges for Data Science and Analytics courses. The country produces some of the best data scientists with the necessary skills and abilities to succeed in a variety of businesses. The Canadian job market features many significant industries that hire data scientists all year long at competitive salaries. As mentioned, data science students can advance their careers to some of the top-paying job opportunities immediately after graduation. For more information, connect with the career experts at upGrad Abroad.
How much is the data scientist salary in Canada for freshers?
Data scientist salary in Canada for freshers starts at approximately CAD 77,000 per year, while most experienced data scientists make up to CAD 137,000 per year. A master’s in data science salary can go up to CAD 199,000 with experience!
Which company pays the highest salary for a data scientist in Canada?
Data scientists can earn an average salary of CAD 80,540 per year in Canada, as per some reports. The Hospital for Sick Children, Shopify, Amazon, and Lighthouse Labs are some of the leading employers in the sector. Meanwhile, data analyst salaries in Canada is lower than those of data scientists. As per reports, data analysts can earn an average salaries of CAD 60,416 per annum.
Is data science a good career in Canada?
Yes, data science is a good career in Canada. According to the reports of the Information and Communication Technology Council, it is expected to be in the top 15 digital occupations in the coming decade. The average pay of a data scientist in Canada is comparatively higher than in other countries worldwide.
What is the maximum salary of a data scientist?
If you are looking into machine learning vs. data science salary, machine learning engineers get higher payouts, but data scientists are also highly paid. The highest salary of an experienced data scientist can be as high as CAD 137,000 annually, while a fresher can earn approximately CAD 77,000 annually.
Rakhee Talukdar is an edtech expert with five years of experience in the education technology sector, focusing on K-12 and higher education systems in various countries, including Canada, USA, Finland, France, and Germany. Her background includes founding a startup and working with early-stage educational ventures, giving her a nuanced understanding of the challenges and opportunities within these educational landscapes. Additionally, Rakhee specializes in helping students craft compelling Statements of Purpose (SOPs) for studying abroad, leveraging her insights into different education systems to guide students in articulating their academic and professional goals effectively. Her comprehensive knowledge and strategic approach make her a valuable resource for students navigating their educational journeys and financial planning.
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