The Data Talent Market Continues Its Ascent

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In addition to being a practicing data science consultant and journalist, I also play the role of educator. I’m currently teaching two university classes in data science, and as I look out to my classroom packed with new learners I think about the timing of their entry into the field. There could not be a better confluence of a factors leading to likely success in a professional endeavor. We’re at an important inflection point in history where a glaring shortage of data-centric skills, coupled with an increasing demand for data professionals, represents a unique opportunity for those willing to make a commitment to “tool up” or “retool” as the case may be, in preparation for a career in analytics.

The good thing is, after all the time and effort, the newly acquired skills will keep on giving because the analytics field shall continue to be in favor for a very long time. The field has tremendous longevity as organizations continue to collect more and more data and increasingly use it as a competitive advantage.

Economic Growth vs. Talent Shortfall

Advancements in AI, data science, and analytics have created unparalleled opportunities, currently driving billions of dollars in economic value, with a projected US$15.7 trillion contribution to global GDP by 2030, as reported by Correlation One’s 2019 global Future of Data Talent report. This growth has created new challenges as companies struggle to build data teams to execute on their data strategies and goals. Undifferentiated talent classifications (e.g. data scientist vs. data engineer), poor role definitions, antiquated methods of talent assessment, and the continued search for the perfect unicorn, all play a role in the data talent shortfall experienced by many organizations.

The data science and analytics talent shortfall is massive and getting bigger, a shortage that can hamstring companies for the next decade or longer:

• 40% of companies claim they are unable to hire or retain data talent due to a lack of supply.
• There is expected to be to another 2.7M new data-related job postings in the United States by 2020.
• There is an expected 20% increase in demand for data talent by 2020.

Data Literacy is King

Even though there is a strong demand for data professionals, there is actually an overabundance of people seeking analytics jobs. The problem is data literacy and a lack of emerging workers who have the full skillset employers need. Apparently, the interest is there, but the education is not.  

It’s becoming apparent that data literacy is becoming essential for businesses to grow. A recent LinkedIn study found that the U.S. has a shortage of more than 150,000 people with data science skills, especially in major tech hubs like New York, San Francisco and Los Angeles. With the demand for talent exceeding supply by up to 50%, increased data literacy is of critical importance moving forward. What’s needed are quality degree programs that will open doors and jump-start careers for eager analytics job seekers.

Being a Data Professional Means Never Stop Learning

But even for seasoned data professionals, the road to continued success is not always smooth. Decades ago, a term was coined for a “perception of fraud or phoniness by a person experiencing success in a senior business role.” The so-called “Imposter Syndrome” is now being discussed as a phenomenon affecting those working in the field of data science. Many of my data colleagues have intimated to me their own feelings of inadequacy. The reason is simple, this field is accelerating at a mind-numbing pace with new programming languages, data platforms/frameworks, algorithms and data tools coming on the scene at a pace where no human can realistically master them all, or even keep their head above water. I can’t think of another field that is advancing at such an accelerating rate.  

Data professionals are looking for ways to keep up. For example, I write a monthly article that offers the “Best of arXiv.org,” the infamous pre-print server for research papers. These articles consistently rank very high in terms of popularity. Why? Imposter syndrome is the culprit. Many data people value a curated list of papers so they can feel like they’re keeping pace with the leading edge of the field.

But the more new books you consume, the more blogs you frequent, the more conferences you attend, the more webinars you watch – the more many data professional have that sinking feeling about what they don’t know. It’s a never ending feedback loop that inserts a degree of uncertainty in people’s professional lives. But there are ways to mitigate these feelings of being an imposter. As many of today’s data professionals have transitioned into the field from other disciplines, one important strategy with which to overcome this syndrome is to solidify your academic background with a formal degree program in a data related field. A degree advances your street cred to a competitive level with your contemporaries and at the same time improves your confidence that you know as much as most others.

Core Ingredients of a Data Degree Program

What can you expect to gain from a postgraduate degree program in analytics? Such programs can propel you into the analytics field by providing foundation subjects as programming, data analysis, and analytics for business. In addition, you can master core subjects like managing data teams, data visualization, data storytelling, and predictive analytics. Supplemental subjects may include decision making and financial modeling. Lastly, and critically important today, is a degree program with a solid focus on the ethical use of data and combating algorithmic bias. Many degree programs take shortcuts when it comes to data ethics, but most agree that this situation must change and give attention to where data comes from, what can be done with it and whether it can be actively or only passively collected.

Conclusion

To anyone feeling excitement about entering the data industry, your time is now. This “candidate’s market” won’t last forever as more people acquire the skills necessary to land a job in the field. In order to take advantage of this market inefficiency, all you need to do is make a firm commitment to the field, and acquire the skills employers are seeking to fill an ever increasing number of analytics job positions. If you don’t have the proper academic background, or even if you want to supplement your existing academic history with a fresh outlook, it’s time to seek out a shiny new degree that can help pave your way to success as an analytics professional.

Contributed by Daniel D. Gutierrez, Managing Editor and Resident Data Scientist for insideAI News. In addition to being a tech journalist, Daniel also is a consultant in data scientist, author, educator and sits on a number of advisory boards for various start-up companies. 

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