Data science is the practice of gathering, storing, sorting, and analyzing data to help companies make data-driven decisions. It is frequently employed by highly experienced computing experts with extensive technical knowledge and experience.
Every encounter in any technical realm has a collection of data. It is a fascinating field to work in today's society. As we all know, in this age of information, data is the key to power.
The rise in the popularity of the field has attracted the attention of many students. Canada has been a popular study destination for a long time, and it's no different for data science aspirants. Every year more and more students go to do their masters in data science in Canada.
Canada provides excellent opportunities for data science students, from quality education & best teaching faculty to the best research facilities & top job opportunities.
In this blog, we are going to take a look at the most attractive data science jobs in Canada. From all job profiles available in the field in Canada to top recruiters for data scientists that will provide you with the best work environment and growth opportunities, this blog will cover all of these aspects with the finest details.
Let's start first by taking a look at the scope of data science.
Scope of Data Science in Canada
Data Science is an increasingly growing field, and some researchers say that the data science field is growing so rapidly that shortly, the demand will increase so much that the global market will face a shortage of data scientists & analysts by around 1.5 million or maybe even more.
In Canada, this process has already begun. The demand for data scientists and analysts is increasing rapidly, but the supply cannot meet this growing demand. This produces a perfect opportunity for a data science student to go job hunting in Canada. Due to a lack of supply, the average salary of a data analyst has also seen a huge spike in Canada.
Canada's economic growth is being driven by technology and innovative companies. According to the Conference Board of Canada, over the next five years, Canada will need to fill over 575,000 new jobs in STEM fields (science, technology, engineering, and mathematics).
This is the beginning of the golden era of data science. Data science is a relatively new field, but it is rising at an exceptional rate, and it is going to continue that way.
This decade is going to be of prime significance in data science; whoever gets attached to it now is going to enjoy its benefits for a long time. And there is no place more perfect than Canada for this.
But before diving right into your research of the best opportunities available in Canada, let's not forget the fact that the employer will also have certain expectations from you, and there will be some key skills that they'll want you to possess before hiring you.
Let's first take a look at the most “ In-demand skills” required to be a successful data scientist in Canada.
In-Demand Skills required for High-tier Jobs in Data Science
There are a lot of skills required to be a data scientist. Every industry and organization requires a data scientist for different things. But there is a base layout that defines the key skills required to be considered a good data scientist. These skills will make you a top pick for any company that is looking to boost its growth with data-driven decisions.
SQL & SQL server:
SQL is the most widely-used language for manipulating data in databases. It stands for Structured Query Language and uses commands like SELECT and WHERE to retrieve information from database tables.
SQL Server is a database management system that allows users to create tables that store information as rows with columns that represent different pieces of information about each row (e.g., name, address).
It also allows users to define relationships between tables using foreign keys so that when one row is deleted from one table, it automatically deletes from related tables too.
You should have at least a basic understanding of how SQL works before pursuing this career path.
Statistics:
The science of generating inferences from data sets depending on their size and complexity is known as statistics. Statistical techniques are used by data scientists across industries to draw insights from huge amounts of information gathered during experiments or surveys.
Statistics is a really important skill to have, and it is something that recruiters expect every applicant to have. So, before applying to any data science jobs, please get a good grip on Statistical knowledge.
Machine Learning:
Machine learning is a type of artificial intelligence that allows computers to learn without having to be explicitly programmed. Instead of requiring explicit programming for each job, machine learning methods allow computers to make judgments based on prior experiences.
Today's world is tech-savvy, and the amount of data is constantly increasing, but every organization wants to save time in processing this data. So, programming their algorithms for each task is very burdensome. Here, the importance of machine learning comes into play, and it becomes a “must-have” skill to possess.
Data Visualization:
Data visualizers help translate complex data into charts, diagrams, and other types of visual representations that can be understood by people with varying levels of technical knowledge.
This skill helps in simplifying the data and making it a lot easier to understand. Companies demand these skills for various purposes e.g., it helps in making the marketing teams easily understand the data and devise strategies based on it.
Python programming skills:
Python is one of the most popular programming languages for data scientists because it has a large library of pre-built modules that make it easy to create tools for data manipulation and analysis.
Python also supports object-oriented programming and has advanced features such as dynamic typing and list comprehensions that make it ideal for solving complex problems.
Data Analysis & Communication:
Data analysts need to be able to analyze large amounts of data, identify patterns and trends, and present them in a meaningful way. They should also be able to communicate these findings to stakeholders.
Creative thinking:
Data scientists must think outside of the box to discern the accurate meaning. They should be able to think differently about problems and solutions. A data scientist must be interested in comprehending data and interpreting it in a variety of ways.
These are the key skills that we have derived from the input from industry experts in Canada. These are the skills that top recruiters in Canada are looking for in a data scientist. There are a lot more skills to learn in the field of data science as it is an ever-growing field, but you will learn most of the other skills as you gain more experience while working with big data.
Top Data Science Recruiters in Canada
The demand for data scientists in Canada is high. There are tons of MNCs and big organizations offering really good opportunities and equally good pay to data scientists in Canada.
Let's take a look at the top recruiters of data science in Canada:
Shopify:
Shopify offers an outstanding work environment with excellent benefits and perks such as paid parental leave and stock options.
It also has a very open culture where employees share ideas freely across departments and levels which helps create a sense of unity and purpose among employees. To top it off, Shopify offers flexible working hours so you can enjoy life outside of work!
Deloitte:
Deloitte is one of the largest professional services organizations in the world with over 200,000 professionals serving clients across multiple industries including financial services, manufacturing, healthcare, and technology. In recent years they have been hiring more data scientists to build out their AI practice within Deloitte Digital which focuses on digital transformation for clients across industries.
TD Bank:
TD Bank Financial Group is one of Canada's Big Five banks with $1 trillion CAD in assets under management globally.
TD Bank's Data Science team was created in 2016 when it hired its first Chief Data Officer (CDO), Jeff Singer from Credit Suisse who now heads up this team along with many other talented data scientists that have helped in maintaining the reputation of TD bank as one of the most successful organizations in Canada and the world.
Hootsuite Media Inc.:
This social media management platform has been growing rapidly since its founding in 2008, which has led to increased hiring needs across all departments. Hootsuite currently employs more than 300 people at its Vancouver headquarters alone — not including its remote workers or those who work remotely from other locations around the world.
Hootsuite recruits data analysts and researchers as well as developers from a wide range of skill sets including Python, Java, and C++.
Tableau Software:
This Vancouver-based software company has been on a hiring spree since 2016 when it expanded its office space by 50%. Since then, it has continued to grow and currently employs more than 550 people across its global offices.
In addition to software engineers, Tableau also recruits business intelligence developers and sales specialists to help expand its sales team and increase the company's impact on a global scale.
Most Popular Job Positions for Data Science in Canada
There are a lot of job positions once you complete your education in data science. Canada is one of the top choices for working a full-time data science job. This is because, in Canada, there are a lot of different job profiles in data science well.
Let's take a look at the most in-demand job profiles in data science in Canada:
Data Analyst:
A data analyst performs data exploration and analysis to help organizations make decisions based on their findings. They may also work with business intelligence tools or software programs like Tableau or SPSS (Statistical Package for the Social Sciences).
- The Average Annual Income for a data analyst in Canada is C$58843.
Data Scientist:
One of the most common positions in data science is data science. Data scientists are responsible for analyzing large datasets and extracting meaningful information from them. They interpret their findings through visualization and provide recommendations based on this insight.
- The Average Annual Income for a data scientist in Canada is C$80214.
Data Engineer:
A data engineer builds software systems that store and process large amounts of raw data from multiple sources. They may also help optimize databases so they run more efficiently or build tools that make it easier for non-technical users to access information stored in databases.
- The Average Annual Income for a data engineer in Canada is C$81870.
Data Architect:
A data architect is someone who designs an enterprise's overall approach to handling information and making sense of it through analytics tools like Hadoop or Spark. A successful data architect must be able to understand how different parts of an organization interact with each other.
- The Average Annual Income for a data architect in Canada is C$101923.
Machine Learning Scientist:
Machine learning engineers are tasked with building machine learning models using algorithms and other tools such as Python or R. Machine learning engineers may also be called upon to create new machine learning models from scratch or improve existing ones based on feedback from users and analysts.
- The Average Annual Income for a Machine Learning Scientist in Canada is C$85660.
Business Intelligence Developer:
An engineer who utilizes business intelligence software to understand and show data for a company is known as a BI developer. This position is suitable for people with experience in data science and software engineering.
- The Average Annual Income for a Business Intelligence Developer in Canada is C$84,671.
Data Mining Engineer:
Engineers that specialize in data mining are in great demand. They are in charge of data design and interpretation for high-volume transactional systems.
- The Average Annual Income for a Data Mining Engineer in Canada is C$71,000.
Pay by Education in Data Science
Although anyone in the data science field can make a decent amount of income. But not everyone gets paid equally. The variation in data science salaries depends on a lot of different factors, such as:
- Job profile they are working for
- The organization they are working for
- The difference in education
- The difference in experience
We have already seen in the article above that how working at different job roles or organizations can require different things from you and will, therefore, have different salaries.
Similarly, the level of education you have also laid a good impact on what your starting salary package will be in the field of data science.
On average, data scientists with a Ph.D. earn more than $70,000 per year. Those with a master's degree earn between $60,000 and $70,000 per year, while those with a bachelor's degree earn between $50,000 and $60,000 per year.
This difference will mostly occur in the initial phases of your career. After that, the quality of your work & the experience you hold will help you in landing a better job and getting higher pay.
Pay by Experience in Data Science
In the long run, experience is what will bear the most fruitful result for you. Data science jobs in Canada are growing at a fast pace, and the salary is also not bad. If you have good experience, then you can expect to earn even more than $100,000 per year.
Data science jobs in Canada offer a great opportunity for professionals who have the right set of skills and experience.
An experienced professional with 10+ years of experience can earn anywhere between $100K – $120K per year, while someone with less than 5 years of experience can expect an annual salary ranging from $40K – $70K per year, depending upon their educational qualifications and experience level.
Experience is the most reliable factor when it comes to hiring. And recruiters tend to bend more towards experienced candidates than freshers. The reason for that is that experienced candidates are easy to manage and require minimal training.
Conclusion
Canada is a worldwide education powerhouse, having some of the greatest universities in the world for Data Science and Analytics programs. Data scientists with the required skills and competencies to thrive in several industries are produced in the country.
Many important companies in Canada recruit data scientists all year long at attractive pay. As previously said, data science students may instantly move their careers to some of the highest-paying job prospects.
For more information or assistance with education abroad, make a call to our experts.
