Wall Street & Technology is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Careers

05:37 PM
Al Nugent
Al Nugent
Commentary
Connect Directly
LinkedIn
RSS
E-Mail
50%
50%

Should I Hire a Data Scientist?

Before spending big bucks on data scientists, understand the depths of the big data problem. Identifying the issues can help extract maximum value from the coveted skill sets.

Contrary to prevailing sentiments, I counsel patience with regards to hiring a data scientist. Firstly, I mean no disrespect to my data science colleagues, and many will likely agree with me because no one likes to enter an environment where sub-optimal results or failure are probable. Yes, it’s likely you need to add one or even a few data scientists to your team, but not as your first step into the wide, wide world of big data. Give me a few minutes and hopefully you’ll see it my way.

Sure, big data is, well big. And it’s scary. Especially to those of you who have not been around large data sets most of your lives. So you need help understanding it.

To put the problem in perspective let’s look at a medical analogy. If you have some discomfort in your chest, you don’t run to a cardiac surgeon and ask for bypass surgery. First you try to understand the nature of the problem and then go through protocols designed to make the discomfort go away. Even in the case of extreme circumstances, one goes through a diagnostic process, perhaps in an emergency room, to determine the best way to get “better.” I would submit that if your business situation is extreme with respect to big data, there are probably bigger issues with which to deal and you might need a different kind of specialist. A lot is going to depend on the size of your company or organization.

If you are a midsized to large global enterprise with lots of consumer-type customers, the need for big data usage may be more acute than in smaller companies, and at some point you may find that you need data science expertise in house. Smaller companies need to think very hard about on staff data scientists as the costs may outweigh the benefits. In either case hiring decisions should follow strategy, planning, budgeting, etc. Knowing what you need to do ahead of time will help to frame implementation decisions down the road, including and especially hiring.

What if you don’t have the knowledge to craft a strategy?

In all fairness a data science perspective will be important in any well-conceived strategy or plan. Hire some consultants. (I know this seems self-serving, but the right consultants will work themselves out of a job. Others, not so much.) The short term expense will be amortized many times over as you march down the road towards extracting maximum value from your big data investments. Not every consulting firm will have the expertise necessary, although many will profess they do.

Like many other decisions we make: buyers beware. Network with colleagues, attend some industry conferences, find the right short-term help and the rest will fall into place. When the time is right to hire, hold on to your chairs. According to the media, it looks like data scientists may be getting paid better than cardiac surgeons; so don’t expect to get any bargains.

Another important point to consider is the nature of big data and big analysis problems. The real challenges may not lie in the interpretation of the data or with some other esoterica only handled by data scientists. One of the most challenging elements of big data environments is the efficiency and effectiveness of complex workflows. If your organization is not adept at handling large amounts of work that need to be decomposed, parallelized, and recomposed iteratively, then the number and quality of data scientists on staff is quite irrelevant. Like many other problems in the technology environment, there is a need for a thoughtful, balanced approach so you can achieve the most value with the least amount of waste.

There really isn’t any need to panic hire. Big data is here to stay. If we have proven anything it’s that as an industry we are insatiable when it comes to capacity, speed, bandwidth consumption, etc. That means you have time to strategize and plan about how to make the most effective use of the big data that matters to you. Remember the old saw: proper planning prevents poor performance. Never has it been truer than with big data.

Alan Nugent is a leading independent member of the Adaptive Computing Board of Directors. He is a senior executive with nearly 30 years of experience in managing and engineering the strategic direction for technology in global enterprises ranging in size from start-ups to $20 ... View Full Bio
More Commentary
A Wild Ride Comes to an End
Covering the financial services technology space for the past 15 years has been a thrilling ride with many ups as downs.
The End of an Era: Farewell to an Icon
After more than two decades of writing for Wall Street & Technology, I am leaving the media brand. It's time to reflect on our mutual history and the road ahead.
Beyond Bitcoin: Why Counterparty Has Won Support From Overstock's Chairman
The combined excitement over the currency and the Blockchain has kept the market capitalization above $4 billion for more than a year. This has attracted both imitators and innovators.
Asset Managers Set Sights on Defragmenting Back-Office Data
Defragmenting back-office data and technology will be a top focus for asset managers in 2015.
4 Mobile Security Predictions for 2015
As we look ahead, mobility is the perfect breeding ground for attacks in 2015.
Register for Wall Street & Technology Newsletters
Video
Exclusive: Inside the GETCO Execution Services Trading Floor
Exclusive: Inside the GETCO Execution Services Trading Floor
Advanced Trading takes you on an exclusive tour of the New York trading floor of GETCO Execution Services, the solutions arm of GETCO.