Best Guide to Getting Data Scientist jobs in Canada – Are you interested in data science jobs in Canada? Data science job in Canada is one of the more promising professions, with an average yearly salary of $94,756. Data scientist jobs in Canada with the NOC code 2172 are one of the most in-demand jobs in Canada because of their professionalism and versatility.
Best Guide to Getting Data Scientist jobs in Canada
To get data scientist jobs in Canada, the first step is to take a computer science degree or a degree in mathematics. Get knowledge of programming, a professional certification, and knowledge of data, and databases.
In Canada, a data scientist job is a high-tech job that sounds complicated, mysterious, and hard to get. Finding employment in data science, especially at an entry-level salary, may be easier than you believe.
Data Scientist Salary
Data scientist jobs in Canada are one of the top-tier professions. As a data scientist, you get an average salary of $94,508 yearly or $48.47 hourly. Data scientist entry-level salaries start at $77,450 per year, with experienced data scientists earning up to $134,550 per year.
Data scientist salary per region
- Ontario $100,000
- Alberta $85,361
- Quebec $85,000
- British Columbia $80,000
Skills needed for Data scientist jobs in Canada
To become a data scientist, you must be familiar with several important programming languages as well as statistical calculations. Strong interpersonal and communication skills must be mastered.
- R programing
- Python Programming
- SQL databases
- Hadoop platform
- Data visualization
- Ability to tell stories for statistical computations.
- Machine learning and AI
- Business strategy
- Good communication.
- Ability to work with teams of an organization.
- Ability to learn new concepts.
Below are the soft and technical skills required for data scientist jobs in Canada.
Data science should be able to:
Unlocking the value of big data
Data becomes more valuable as society becomes more data-driven, but only if it can be used in real-world business applications—the data scientist steps in at this point.
Businesses need people with statistics and data modeling knowledge to find value in complex, unprocessed data from many sources, such as machine log data, digital media and documents, databases, the web, social media channels, and the Internet of Things (IoT) sensors.
Organizations also use these insights to improve cybersecurity, keep employees, increase productivity, and find new employees.
There should be many technical skills. Read below for the technical skills required.
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Diverse technical skills are required
Of course, this position calls for technological skills. Data scientists need to know a lot about different types of analysis and math, like multivariable calculus and linear algebra.
In essence, data science is a synthesis of statistics, mathematics, and computer science. As a result, many organizations particularly search for employees with statistical skills.
Businesses need people who know statistics and data modeling to unlock the value of complex, unprocessed data from different sources, such as machine log data, digital media and documents, databases, the web, social media channels, and the Internet of Things (IoT) sensors.
Data scientists with expertise in Oracle, Microsoft SQL Server, and Hadoop and Extract, Transform, and Load (ETL) abilities, such as designing database schemas and developing systems, are in great demand.
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What do data scientists do?
Data scientist jobs in Canada: Data science is a field that combines knowledge of a subject, skill with computers, knowledge of math and statistics, and the ability to get actionable insights from data.
Are you considering becoming a data scientist in Canada? Read more for all you need to know about what data scientists do.
AI systems are made by putting together numbers, text, images, video, audio, and other data with machine learning algorithms to do things that would usually require human intelligence.
In other words, these technologies generate insights that analysts and business users can use to generate revenue.
First, you need to be aware that data scientist jobs in Canada require skills. Robert Half’s most recent Salary Guide says that there is a lot of hiring going on in the technology sector, with employers hiring technology professionals at or above their levels before the pandemic.
Data scientist jobs in Canada are one profession that involves experts and is required by businesses in all major industry sectors, from technology and manufacturing to financial services and healthcare, as well as by institutions in academia, government, and nonprofit organizations, as businesses quicken their digital transformation.
Education requirements for advanced data scientist roles
Many businesses prefer to hire data scientists who have doctorates in fields like computer science or mathematics.
A doctorate can give candidates an edge in hiring, and it’s an absolute requirement for some roles.
Even though you might not need a graduate degree to get hired as a data scientist at the beginning of your career, it is likely to become more important as you try to move up in the field.
Ways to gain relevant knowledge and skills
Here are some ways to get the right knowledge and skills and improve your chances of starting a successful career in data science:
- Stay current with online resources.
Look for e-books, online courses, and video tutorials that dig deeper into online data analysis, statistics, data coding, and related topics that interest you. (Examples of resources offering online learning options for data science include Coursera, DataCamp, edX, LinkedIn Learning, and Udacity.)
- Learn relevant programming skills
Becoming proficient with fundamental languages like Python and SQL will likely be essential.
But also look at the job descriptions of data scientists at the organizations you’d like to target for employment.
What other types of languages do they expect for entry-level roles? That will give you a better sense of where to focus your learning.
- Get to know the data science community
Look for opportunities online to connect with people who work in data science or who want to work in data science.
You might check LinkedIn groups for data science professionals or consider reading data science blogs and following influential data scientists.
When you know some well-known data scientists, you could ask them for informational interviews to find out more about their jobs.
Also, don’t overlook the peers, mentors, and professional contacts already in your professional network. They might have suggestions for breaking into the data science field—and they can put you in touch with relevant contacts they know.
- Start your data science projects
Putting together your own data science projects shows that you want to learn, which can give you an edge when it comes to getting hired.
It indicates to employers that you are committed to learning new skills and applying them in creative and innovative ways just because you love them.
A quick search online can help you find a wealth of ideas for data science projects for beginners.
Top 5 Cities for Data Scientist Jobs in Canada
After thinking about immigrating to Canada, the next thought that comes to mind is, where are Canada’s best places to work as a data analyst? A survey found that Toronto, Ottawa, Vancouver, the Waterloo region, and Montreal are the best places in Canada to find jobs in technology.
- Toronto
About a quarter of all new IT jobs in Canada have been made in this city alone.
- Ottawa
Ottawa has an incredible 11.3 percent of tech professionals, which is more than double the average of 5.6 percent for Canada and the most of any city in North America.
- Vancouver
Microsoft, Amazon, Apple, Facebook, Cisco Systems, Samsung, SAP, Intel, Salesforce, Eventbrite, Absolute Software, ACL Service, TELUS, Hootsuite, Dwave, 1Qbit, and Slack all have their headquarters in Vancouver.
- Waterloo
With only 22,400 tech workers in the Waterloo area, competition isn’t as fierce as in other markets.
- Montreal
People say that Montreal is the video game capital of North America. The city puts on three digital festivals, has several cultural institutions that focus on certain things, and has more people with smartphones and who use social media than the rest of Canada.
Pathways to Immigrate to Canada as a data analyst
- Express entry
But the fastest and most common way to move to Canada is through the Express Entry system. You only have to make an Express Entry profile and choose the right one.
The Comprehensive Ranking System (CRS) also gives candidates points for being eligible. You don’t need a job offer to join the Express Entry pool or be chosen.
People who already have jobs are better off in the CRS.
You can pick any of the three options for your profile. This is a federal program for people with skills.
- Canada experience class (CEC)
- Federal skilled worker program (FSWP)
- Federal skilled trades program (FSTP)
Most importantly, if you want to move to Canada as a database administrator, the FSWP is the best way to do it.
Provincial Nominee Program
With the provincial nominee program, you can become a database administrator in Canada and then move there. You can live and work in the province if you want to.
Canada’s provinces run a “provincial nominee” program to attract workers who want to move to their province.
Each province in Canada has its own nominee program. Find out more about the requirements for Canada’s different nominee programs.
Conclusion
Everything discussed here on how to become a data scientist in Canada can put you on the right track to building your career.
Think about contacting specialized tech recruiters for assistance as well. They can connect you with local organizations and employers who may be hiring for entry-level roles and also provide valuable job search tips.
Imagine that you are in college or just graduated and want to know how to become a data scientist. In that case, the most important job requirements will depend on the employer, the company’s data management tools, and whether or not the business has the time and money to train entry-level data scientists.
