How To Become A Data Scientist In Canada from scratch?

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How To Become A Data Scientist In Canada from scratch?

How To Become a Data Scientist In Canada from scratch? Can I become a data scientist without a degree in Canada?

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Data science is a rapidly emerging field that combines several prevalent career avenues such as a business, data, programming, logic, and statistics.  Therefore, if you are considering a career in data science, it helps that you have an interest or some experience in these fields.

Data science goes way beyond analytics.  It constitutes deep statistical analysis and discovery, using complex algorithms and codes to solve extremely complex data problems.  The crux of the profession is all about finding and articulating evidence regarding findings and being capable of communicating or explaining such information in a succinct way.  Data scientists are often required to act on their findings; therefore, having exceptionally strong decision-making capabilities is important too.

This article explores how to land an amazing data science role, what you need to do to enter the profession, how to gain qualifications, and further expand your data science career.

How To Become A Data Scientist In Canada from scratch

How To Become A Data Scientist In Canada from scratch

How to become a data scientist from scratch in Canada

There is a certain amount of ‘pre-work’ that can be done to prepare yourself for a career in data science.  Having a general education diploma GED) or being a secondary school graduate will certainly help, but if this is already far in the past then refreshing yourself on subjects such as mathematics, science and English will definitely help.  Seeing as a large chunk of data science rests in programming skills, getting a head start on this and learning about the most common programming tools (such as a Java or Python) will be hugely beneficial.

The next thing to think about is some form of undergraduate or further education studies.  The subjects most aligned with data science are mathematics, statistics, computer science, information technology or data science itself.  Completing some form of diploma, certificate or bachelor’s degree in one of these subjects will give you a huge amount of professional credibility and clout.

As you complete your studies, you will want to start thinking about getting an entry-level job in data science.  Competition for these jobs is fierce, so you will need to ensure that any experience and your education stand out from the crowd, and that your resume, cover letter and LinkedIn profile will sell you to the fullest extent.  When searching for a job, being able to showcase your continuous professional development (CPD) is vital.  Demonstrating that you understand supporting facets of data science and have taken supplementary learning to further your knowledge will ensure that your application gets noticed.

Once you find that first rung on the career ladder, you will then need to think about taking on further education or masters-level studies.  Having a higher level of focused data-science education will mean that you are best-placed to land more senior or higher-paying jobs in the future.  In addition to this, networking and building your profile as a credible data professional will also help you climb up the hierarchy.  Continuously building your skill profile and gaining knowledge such as leadership or project management, will mean that you will begin to be perceived as versatile and adaptable to different data science careers, positively impacting your earning potential.

Data science learning paths and courses

Most Canadian universities offer data science bachelor’s and master’s degrees; two stand-out offerings are masters courses at the University of British Columbia, the University of Toronto and the University of Western Ontario.  Nevertheless, there are some other elements to the data science learning path.  Learning programming can be done remotely, such as through Google’s Python Class.  You also want to think about learning database knowledge, such as Structured Query Language (SQL).  Again, database skills are available online, such as through CodeAcademy.  As mentioned before, you could refresh your mathematics skills too.

Other elements further along the learning path could be subjects more nuanced to data science such as version control, machine learning, time series and deep learning.  There are also specific data science courses available via Coursera, which can provide a quicker and more cost-effective way to break into the profession.

Where to find data scientist jobs in Canada

Canada boasts a comprehensive employment market and benefits from high usership of some of the most popular job boards.  As such, there are plenty of data science jobs posted on LinkedIn, Indeed and Glassdoor.  A large part of finding data science jobs is in the quality of your resume and cover letter, so take some time to ensure these documents completely reflect your career goals, and maybe even consider having them professionally written if possible.   Networking is also critical.  Where possible, connect with data science leaders on LinkedIn, an begin to build your career brand.  This will ensure you are in pole position for any opportunities that come up.

Conclusion

Data science is a very rewarding career but requires a high level of qualification and tenacity, to cope with the level of competition for the best roles in the profession.  The best strategy to break into data science is to prepare thoroughly, and work on gaining education or experience that will ensure that you have your foot in the door to progress up through ranks.  The rewards will follow!

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