Navigating the Numbers: A Comparative Analysis of Data Science Job Trends in Toronto vs. North America

Last month I wrote a blog called, ‘The Future of Data Science: Job Trends, Skills, and Technologies You Need to Know’.  Its primary aim was to provide context and familiarity around the data science job market.  It emphasized the on-going importance of staying informed about the evolving landscape of the field, adapting to technological advancements, and acquiring in-demand skills to thrive in the dynamic and competitive industry, making it relevant for both beginners and seasoned data scientist professionals alike.

A Critical Success and a Must Read:  What the Blog Focused On

I think it was enormously helpful.  One person who read it said it was ‘riveting’, ‘wildly informative’ and that the author showed ‘great skill in conveying the material.’  Full disclosure:  that person was me.  Understandably, I think it’s definitely worth a read, so just in case you missed it, you can find it here:  The Future of Data Science

By way of a quick recap, we scraped a jobs website to gather recent, detailed data on North American data science job postings, covering aspects like locations, salaries, experience requirements, educational qualifications, and sought-after technical and soft skills; the aim of which was to identify trends and monitor the evolving job market through a monthly report.  Incidentally, you might be able to subscribe to that jobs report very soon.

What the Blog Did Not Focus On: Toronto Vs. Everyone

Given that last month’s blog was a sort of introductory one, it focused on all of North America.   In doing so, it offered a broad North American perspective without delving into possible distinctions between the US or Canada, or specific regional details.  So, this post will take up the latter and  zero in on Toronto’s data landscape.

Why Toronto? Well, that’s where I’m from, so I guess this blog will be a bit self-serving. But being from Toronto, there’s a popular and expensive shirt (everything is expensive in Toronto) that reads “Toronto vs. Everyone.” It’s meant to signify a little local pride; if anything, the sentiment may have rubbed off on me a little bit.

No need to fret—this blog stays relevant even if you’re not a Torontonian. It compares the city to the broader North American market, delving into aspects like salary, monthly job availability, and the major job providers. This way, we’ll uncover both commonalities and distinctions in each group. So, let’s dive in without further ado…

Question 1:  What Are the Biggest North American Job Markets and Where Does Toronto Stand?

Just exactly how big is Toronto’s data science job market compared to other major North American cities? Given that Toronto ranks as the fourth-largest city on the continent, serving as Canada’s business and financial hub with the second-largest financial center and the third-largest tech sector, one might expect it to stand out among its North American counterparts—and indeed, it does!

Over the months of August and September,Toronto had the third highest number of data science job postings.  Only New York and Washington had more postings over the same period of time.  It even managed to beat out the tech mecca of San Francisco.  Not too shabby!  These numbers and Toronto’s position would seem to affirm its competitive standing among major North American cities.

Question 2:  What about Salary?  

Considering Toronto’s prominence as a hub for job opportunities within North America, one might wonder if it translates into better compensation. Answering this question, however, proves challenging, primarily because salary information for data science positions in Toronto isn’t abundantly available. It’s not that the rest of North America provides an open book on this matter either, but Toronto, in particular, reveals a scarcity of such information.

Diving into the details of 317 job postings in Toronto, only 41 (approximately 13%) disclosed salary information, revealing a notable scarcity compared to the broader North American market. In contrast, 40% of the 13,186 job postings across North America provided insight into salary expectations.

Given the modest sample size in Toronto, it’s important to approach this analysis with a ‘grain of salt’. Despite this limitation, intriguing patterns emerge. Toronto demonstrates a consistent trend of higher salaries across various quantile ranges, outshining the North American average. This trend holds true even when examining the average salary, where Toronto, with an average salary of $110,610, outperformed the North American average of $102,543. 

Alright, but how does that Toronto average salary compare against the largest local job markets, specifically?  Not too bad, actually.

The Toronto average salary, while not claiming the top spot, holds its ground. Taking the fifth position in the lineup, Toronto’s compensation landscape proves robust, especially when you consider the fierce competition in major job markets. Having said that, I guess it’s no surprise that San Francisco holds the top spot here. 

Question 3:  How In Line is Toronto with Overall Trend in Month to Month Job Postings?

With this question, we’re peeling back the layers of the Data Science job market to observe its monthly ebb and flow, specifically examining if Toronto mirrors a broader trend. The short answer is yes – unfortunately.  Why unfortunately?  Because the overarching pattern indicates a decline in the volume of job postings compared to the preceding month. As illustrated in the chart below, a discernible 18.65% downturn in job opportunities has unfolded from the previous month.

More unfortunate for Toronto however, is that it seems to be leading this trend with a 30.43% decline in data science jobs from the same time.

Now, let’s dive deeper into the specifics and unpack the diverse job titles observed across our two-month span.

Upon closer inspection, a comprehensive downtrend becomes apparent across various job types: Data Analyst, Data Engineer, Data Scientist, and Machine Learning Engineer. The most pronounced dip occurred in the Data Analyst domain, experiencing a substantial 24% reduction. Meanwhile, the roles of Data Engineer and Data Scientist showed a relatively comparable performance, each witnessing a decline of around 15% and 18%, respectively. Machine Learning jobs experienced a comparatively milder downturn, registering a 12% decrease.

Looking at the Toronto market, the landscape contains a few intriguing variations. Despite Data Analyst roles experiencing the most substantial decline once again, Toronto witnessed a notably larger drop, registering at 38%. In parallel, Machine Learning Engineering posts followed closely with the second most significant drop, marking a decline of 33%. Data Engineering jobs secured the third spot, experiencing a 27% reduction.

Adding an interesting twist, the realm of Data Science jobs in Toronto maintained a noteworthy resilience. The total number of jobs remained virtually unchanged, shifting from 21 postings in August to 20 postings in September, indicating a modest 4% decline compared to the broader trend.

As we unpack the trends over the past two months, both the North American and Toronto markets reveal a decrease in job postings. However, with this limited dataset covering only two months, the critical question lingers: Was September merely a ‘slow’ month, or does it signify a precursor to a broader shift? The hope, of course, leans towards the former, but only time will tell.

Question 4:  Who Are the Biggest Players?

This final question addressed the major players, unraveling the companies that lead the charge in job offerings. Is there a discernible difference in the types of companies driving Toronto’s job market compared to the broader North American scene? Let’s uncover the dynamics.

In Toronto, the spotlight brightly shines on finance-related entities, with banking and financial services clinching the top five spots. However, the narrative expands beyond, encompassing the education sector represented by stalwarts like the University of Toronto and University Health Network. Further diversity emerges with the presence of recruitment and staffing companies like Procom and ISG Search Inc. Telecommunications juggernaut Telus completes the roster, rounding out the top 10 with its influential role in Toronto’s employment landscape.

Zooming out with a broader lens, the largest hiring companies across North America paint a slightly different picture. While financial services heavy weights like Deloitte and Capital One secure their spots, the dominant forces shaping this landscape belong to the realm of ‘Big Tech.’ Apple claims an indisputable lead, towering above the competition with the highest number of job postings. The tech behemoths Amazon, Google, and TikTok also carve their presence, solidifying their influence in the top 10 lineup.

And just before we wrap up, let’s take a quick glance at the job preferences among the top 10 companies in each market. It’s a nuanced exploration of the roles these giants are keen on filling.

Intriguingly, the standout observation lies in the unmistakable tilt of ‘Big Tech’ corporations. These technological powerhouses, including Apple, Amazon, Google, and TikTok, display a pronounced penchant for recruiting Machine Learning Engineers. This emphasis on ML expertise underscores the critical role these companies assign to machine learning in their operations and innovation.

Contrastingly, the banking sector, a formidable force in both markets, seems to chart a different trajectory. Despite being influential players, banks and financial institutions within the top 10 are not notably prioritizing the hiring of Machine Learning Engineers. The juxtaposition of these hiring trends sheds light on the diverse strategic priorities of companies across sectors, each contributing its unique essence to the dynamic tapestry of the job market.

Conclusion: Decoding Toronto’s Data Science Dynamics

In wrapping up our analysis, the unique role of Toronto in the data science job arena comes into sharper focus. As we delve into the key metrics of job postings, salary landscapes, and prevailing trends, Toronto emerges as a contender with its distinct patterns.

Toronto’s Job Market Standing:

Toronto has notably secured the third position in data science job postings over the last two months, positioning itself just below New York and Washington, even managing to surpass San Francisco in job postings. This ranking speaks to the city’s prominence as a hub for data science opportunities in North America.

Salary Realities in Toronto: 

While the salary analysis encounters some hurdles due to a limited disclosure of salary information, the available data indicates Toronto’s competitiveness. The city consistently registers higher salaries across various quantile ranges compared to the broader North American average. This hints at a remuneration landscape that recognizes and rewards data science professionals in Toronto.

Navigating Trends Amidst a Downturn: 

In sync with broader North American trends, Toronto experienced a decline in job postings. Leading this dip with a 30.43% reduction, the city faces the challenge of adapting to a momentarily contracting job market. The decline touched various roles, with Data Analyst positions taking the biggest hit. However, Toronto’s Data Science jobs remained resilient, showcasing a minimal 4% decrease.  Only time will reveal if this downturn is a mere hiccup or a harbinger of sustained change.

Players on Toronto’s Stage: 

In the realm of major players, Toronto’s stage is dominated by financial entities, mirroring its status as Canada’s financial capital. The list includes prominent banks, the University of Toronto, Telus, and entities from the education and recruitment sectors. This local cast contrasts with the more diverse ensemble on the broader North American stage, where ‘Big Tech’ giants hold sway, each playing its unique role in the unfolding narrative.  The difference in hiring preferences was also apparent – ‘Big Tech’ leaned towards Machine Learning Engineers, while the financial sector exhibited a different focus.

Final Notes on Toronto’s Data Science Landscape:

Ultimately, the Toronto versus North America narrative mirrors the popular spirit captured by the city’s favorite shirt: Toronto vs. Everyone. While this exploration might be rooted in local pride, it goes beyond a narrow celebration. It delves into the intricacies of Toronto’s data science scene, shedding light on its position compared to North American counterparts. The tale unfolds, evolving alongside the data, crafting a dynamic storyline for those navigating the numbers in the ever-changing landscape of data science.

Final Final Notes:

Given that this blog revolved around Toronto and the Data Science jobs market, I just wanted to shamelessly plug WeCloudData,(aka, the Toronto Institute of Data Science and Technology), the company I am a part of, largely because as an educational institution it translates into data jobs.  Founded in Toronto and now operating internationally, this is evidenced by a recent Ontario Private Career College graduation and Job Rates survey, which showed an amazing 91% graduation employment rate, and that those graduates were all working in the data field.  Full disclosure:  I am one of those graduates.  In any event, I invite you to look at the link yourself if you are considering entering the data science job market, or if you are already working in that space, but would like to learn new skills, or strengthen existing ones.  Here is the link: Graduate Satisfaction.  Ok.  That’s it.

Thanks for taking the time to read this blog.  As always, I hope it helps!