Knowledge Center: Article
Big Data & Analytics
Big data talent: What you'll find in four different industries5/6/2014
The demand for talent & analytics is at an all-time high and shows no sign of slowing down. That much has become abundantly clear in recent months as we’ve partnered with clients from a wide range of sectors — technology, financial services, industrial, life sciences, healthcare, professional services — who are looking for people to staff and lead their data science teams.
We’ve seen commonalities in skill sets with specific industries. When seeking big data specialists, here is an overview of what you might find:
Academia & Research
The talent in this industry can be described as brilliant, theoretical and quantitative. We find well-educated, technically sound individuals who are brainstorming next-generation analytical models (machine learning, natural language processing, predictive analytics) to better understand quantifiable data. This talent pool tends to excel in idea creation but have limited experience in commercialization and almost no connection to “the business.”
In many cases, the most respected people have been with their current employer for years or even decades, making it difficult to attract them to a new employer. Career motivation factors are different as well: opportunities for research, discovery and published papers are preferred to cash/equity-rich offers and public fanfare.
This industry tends to attract talent that is process-oriented, innovative, technical and comfortable with complexity. The sector offers a robust pool of data talent, many of whom have been doing big data since before it took on that name. Today, almost all major banks, hedge funds, insurance firms, exchanges and credit card companies are in full hiring mode for data scientists, chief data officers and chief analytics officers. Asset management firms, consumer finance companies and credit unions are slightly behind the curve when it comes to data analytics strategy, but most have a steadily growing appetite.
Big data talent working in the financial services sector have an analytical view of the world, whether looking at markets, news events, industry trends or consumer behavior. Those with expertise in the decision sciences are of particular interest to other industries.
Big data talent in the technology sector can be characterized as entrepreneurial, visual and fast-paced. Overflowing with start-ups and well-established giants, the tech world continues to produce the most desirable, innovative talent. Every day, new ways of processing, organizing and visualizing information are created by 20-somethings in Silicon Valley, Boston, Austin and other technology hotbeds.
Publicly traded industry titans ensure that their people are extremely well compensated with long-term equity, so it is nearly impossible to lure talent away from them. At the same time, big data and analytics start-ups are receiving a massive amount of attention, if not overvaluation, because of the potential payday. As a result, it is particularly difficult to recruit talent from venture capital-backed firms on the pre-IPO track.
Consulting & Professional Services
When describing talent in the consulting world, words that come to mind are conceptual, C-level, strategic and commercial. Consultants see it all. Excellent at mapping out data strategy, they often present solutions to business problems through the use of technology.
Many who are thinking about hiring an individual from a consulting firm want to know whether he is capable of implementation and delivery, as well as information strategy. From a consultant’s perspective, the challenge of truly partnering with other business leaders in shaping desired outcomes can help sway her into joining an enterprise.
We found the distinct skill sets for these industries intriguing given the growing demand for big data talent. As firms continue to build internal big data functions through talent acquisition, it’s helpful to consider how specific industry skill sets may complement your own organizational needs.