Opinion: Why a Data Scientist is the hottest job in tech right now

Jan 21 2020, 12:34 pm

Written for Daily Hive by Steve Astorino, vice president of Development, Cognos, and Planning Analytics at Hybrid Data Management and Director of IBM Canada Labs, the largest software development organization in Canada. He is the co-author of “Artificial Intelligence: Evolution and Revolution


Harvard Business Review once called Data Scientists “the sexiest job of the 21st century.” So what exactly is a data scientist, and what makes it such a hot job in today’s market?

Despite its rise across Canadian and global business sectors, data science is still largely unknown or misunderstood by the public at large. In one sentence, a data scientist understands how to collect, use, and analyze data using a machine learning model to solve real-world problems.

A quick online job search for “data scientist” in any of Canada’s major cities garners hundreds of hits for well-paying positions in insurance, finance, auto, shipping, travel, utilities, and education. Even the legal field is snapping up data scientists as fast the market can meet demand, as it moves to greater automation of contract reviews and other tedious, expensive tasks.

The rise of emerging technologies like artificial intelligence and machine learning are already creating a hiring gap in talent capable of navigating these digital technologies. The Information and Communications Technology Council (ICTC) identifies data scientists among the 15 top digital jobs in demand through 2023. The ICTC also foresees demand for digitally-skilled talent in Canada to reach more than 305,000 over the same period. This trendline is playing out as top employers woo employees with digital-first skill sets in the hope that they can weather the storm long enough for employee supply to match demand.

Data science roles are exploding because Fortune 500 companies are sitting on vast amounts of untapped proprietary data. Most companies aren’t yet leveraging the powerful insights hidden within their data, which is where data scientists come in. These companies need experts to help structure and analyze their data, combine it with machine learning and artificial intelligence tools, and produce trustworthy predictions and insights. Better predictions and insights lead to greater efficiencies, lower operating costs, and can transform services to their own clients, allowing companies to leap ahead of their competition.

The advice I give to students and new graduates interested in data science is to never stop learning, especially because the field is so broad. Check out the expanding Data Science programs now offered at post-secondary institutions, from continuing learning certificates to specialty bachelor and master’s degrees. As a side note, universities across Canada must do more to expand and strengthen their data science programs, as the pace of innovation within academia has yet to meet market demand.

Surprisingly, it doesn’t take a PhD in statistics to be a skilled data scientist. A starting point is gaining a solid grasp on the coding tools behind machine learning — R, Python, Spark, Tensorflow, Kubernetes, and more. There are many free or paid online courses that introduce these programs. Equally important to technical courses are business and communications learning, as well as work experience on real data problems. Data scientists make the most impact when they combine domain knowledge — particularly in sectors like healthcare, retail, manufacturing — and data science expertise to drive insights that lead to better decisions.

The ideal data scientist also has excellent soft skills. The ability to relate to others matters because a data scientist must take the time to listen to clients — or business units and executives within a company. Similarly, she should be able to explain machine learning to any audience, not just technical experts. Without the interpersonal skills to understand a business challenge and explain the solution from the client’s perspective, a data scientist might end up solving nothing.

Remember, the definition of a “data scientist,” continues to evolve, so use that to your advantage when choosing a university program or carving out a role within your company. Leading data scientists will tell you they’re constantly discovering more to learn about their specialty.

Data science offers a deeply fulfilling career where the more you learn, the more you can learn. Coupled with new academic and non-traditional education opportunities, more students are choosing data science and helping to close the digital skills gap to keep Canada competitive in the highly competitive global marketplace.

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