Data Scientists in Demand: ‘It’s their time to shine’
According to executive search firm head Linda Burtch, the job prospects for data scientists and other elite analytics professionals have never been better – and the future is even brighter.
By Peter Horner
|Linda Burtch, founder and managing partner of Burtch Works.|
In April, the executive search firm Burtch Works released the results of its first-of-its-kind salary and demographics survey of data scientists, a follow-up survey of big data professionals conducted a year earlier. Among other findings, the 2014 survey quantified that data scientists are well paid, relatively young, overwhelmingly male and that almost half (43 percent) are employed on the West Coast.
Linda Burtch, managing partner of Burtch Works, has been involved in the recruitment and placement of high-end analytics talent for 30 years. She started her career with Smith-Hanley before founding her own company five years ago. Analytics magazine editor Peter Horner interviewed Burtch in April, not long after the survey of data scientists was released. Following are excerpts from the interview.
What did you find that surprised you the most from the salary and demographics survey of data scientists?
First of all, I find it funny that everyone is interested in salaries and what data scientists and big data professionals make, but it’s such a taboo subject to actually talk about. Not to me. I talk about salaries all the time. That’s my business.
What surprised me? That’s an interesting question. It actually turned out the way I thought it would – a lot of the candidates living out on the West Coast and a higher predominance
of Ph.D.s among data scientists than the general analytics population or the big data professionals, as I call them. It all pretty much made sense to me. It was interesting because it was actually quantified.
Weren’t you a little surprised by the extent of the concentration of data scientists – nearly 50 percent – on the West Coast?
That’s for the moment, for now, but watch and see what happens. Analytics has been around for a long time, yet some people still ask me, “Are you sure this isn’t a fad?” It’s not.
Analytics has become a hugely profitable specialty area within organizations as they try to optimize their operations, or target their marketing or look at return on investment issues, and that has been around for years and years.
I would argue that those issues are sort of the humdrum stuff of analytics. Data-driven decision-making is really going to explode, and that’s what we are seeing with this whole area going toward data scientists. Data storage has become so much cheaper, computing power has become much faster, nanotechnology and sensors are now becoming ubiquitous. Self-driving cars, traffic sensors, the energy grid. The list goes on and on and on.
Right now the obvious stuff is happening with understanding digital streams of data in applications related to social media. That’s pretty straightforward stuff, but wait until it hits the healthcare industry, for example. Self-driving cars are going to be a huge, huge deal. While a lot of it is being done out in California now, over the next five years we are going to see it scattered all over the United States.
When it comes to recruiting candidates and job placement, who are you talking to?
I recruit in analytics – people who have master’s degrees in statistics, operations research, econometrics, people who are out there working in business applications, solving problems related to marketing spend or credit worthiness or target marketing. More recently I’ve gotten into data science. That’s a huge umbrella description.
You mentioned operations research, the heart and soul of INFORMS.
It is. When I started out in recruiting more than 30 years ago, I focused on operations research candidates. It’s grown pretty dramatically since then. They have a very fond place in my heart because that’s how I got started. It’s one of those things that I’ve really been involved with – the INFORMS group back in New York when I was living there, and I’m really excited now because the INFORMS group in Chicago is getting re-energized. It’s really exciting to watch.
When looking at the job marketplace, do you distinguish between, say, a data scientist and other analytics professionals?
Let me back up a little bit. Last summer, when I was putting together the big data salary study, I saw that data scientists were a breed apart, and that they had higher compensation levels. So I made the decision to take them out of the general big data study and hold them for later because it’s such an emerging field that’s so different. They are working with what I would call unstructured data. You could get into a lot more detail over how a data scientist is different from a big data professional, but the primary distinguishing feature, in my opinion, is that data scientists are working with data that’s unstructured. It’s something that’s going to grow as sensors become more and more prevalent and data streams become continuous in so many applications areas.
How would you describe the current job market for quants, for lack of a better word?
It’s hot. A couple of months ago we did a flash survey in which we simply asked how often are you are contacted about a new job opportunity through LinkedIn. We had 400 responses; 89 percent of the respondents said they were contacted at least monthly, and 25 percent said that they were contacted at least weekly. I’m working with elite data scientists, and they’re telling me that they get calls once or twice a day from recruiters, so it’s just crazy.
Our candidates are seeing a 14 percent increase in salary when they change jobs, so there’s a lot of churn out there. If they stay with their existing company, they might see an annual increase of between 2 percent and 3 percent, so the 14 percent is a nice bounce if they decide to make a change. One of my data scientists in Boston said he received 30 calls in one week after he left a job and went on the job hunt.
It’s amazing. Competing offers is another sign that the market is really hot. Sign-on bonuses are another thing that has become very commonplace in the analytics job market. Another sign that is important to note is the academic institutions have really stepped up with many of them developing master’s programs in analytics, predictive analytics and the like, so that’s something that is very new in the last two or three years.
In an interview with the New York Times, you said in reference to MBAs, and I quote, “In 15 years, if you don’t have a solid quant background, you might have a permanent pink slip.” That’s a little rough, isn’t it?
I know, I’ve become the harbinger of the permanent pink slip. Seriously, I have seen many MBAs, your general MBA, look around and say, whoa, this is a little bit scary, because they are seeing this trend toward analytical decision-making becoming so predominant in business. Personally, I think within 10 or 15 years if MBAs don’t have a quantitative foundation, they will be prevented from promotion. We’ll see. I always said back when I was working with the operations research people that my guys are so smart, they are the ones who should be running these companies. Now I’m seeing it come true.
In an episode of the TV show “Mad Men,” the ad agency employees, circa late 1960s, were concerned that a new computer the size of a conference room would make them expendable. Your quote reminded me of that.
Right. A lot of people ask me about that. There is going to be a disruption. There already has been. Just yesterday, the Times had a visual display of analytics and quants and how it was disrupting things and what jobs were going to be eliminated, including truck drivers and airplane pilots.
Self-driving cars, robots, analytics, algorithms and all this stuff is here to stay, and it’s only going to get bigger, but it’s not going to replace the ability to read, write and think critically. While I’m a big proponent of analytics, communication will continue to be really important; human-to-human contact can’t be replaced, ever.
Just how important are communication skills to a data scientist? INFORMS, for example, now routinely holds “soft skills” workshops aimed at helping analysts explain their work to non-technical audiences in order to garner corporate buy-in.
Yes. That’s absolutely critical. The other piece that goes hand in hand with that is having the ability to understand the business at hand. Business acumen is really important. You have to have that gut check; does it make sense and how can I best monetize the situation to benefit a client or employer? It’s really important for people to understand not only what’s interesting – what a lot of quantitative people tend to gravitate toward – but also what’s important.
If a company is just starting out on the analytics journey and has no in-house expertise in this area, how can they judge a candidate’s technical abilities?
That’s an interesting problem. When I’m talking to a client, especially in this data science area that is so new, they will call me and sometime they will have it down. They are talking the right language, they are thinking about the right things, they are asking the right questions. Other clients are floundering; they are still exploring.
I think it’s very important that they make sure they understand where their needs are before they actually bring in somebody because it’s not inexpensive to apply analytics in an organization. You really need to think very carefully what the goals are, what the road map is going to look like and so on. I can certainly help with that, and I can give the names of consultants who can help a company really understand what their plan should be before they jump in and make hires.
On the other side of that coin, what’s the best advice you can give an analytics candidate who is testing the job market?
Another flash survey we did focused on understanding what motivates people to make a job change. The number one motivation is money, but it’s quickly followed by challenging work and the opportunity to grow within an organization.
Money is important to everyone, but candidates shouldn’t make decisions regarding changing jobs based on salary alone because money isn’t going to be the factor that’s going to change their life. Rather, it’s the kind of work you will do and how engaged you will be. It’s really important to understand the challenge and the growth opportunity within whatever it is you are looking to jump into.
The third thing I think is important to analyze for any quantitative person when they’re talking to a potential new employer is to understand if analytics has a seat at the corporate table. You have to make sure that there is buy-in within the organization and the stakeholders are really actively involved and engaged in conversations about how analytics can and should be used or imbedded within any organization. That’s a huge factor in understanding how happy you will be in your job and how successful you can be as a quantitative professional.
Getting back to the plight of the quant-poor MBA, how can a candidate boost analytical skills mid-career? Many colleges and universities are now offering analytics programs, often online, through their business schools, and INFORMS, for example, holds continuing education courses in the analytics area, as well as a certification program.
I get that question a lot: “I’m really interested in beefing up my analytical skills so what should I do?” As you noted, there are more opportunities than ever to do that. In addition to the formal education programs, there are plenty of good books on the topic. I get the question all the time: What books should I be looking at?
Another way that you can jump into this is through Kaggle competitions, which I recommend to people if they are interested in understanding data science and who else is out there doing this kind of work and what they are doing. There are many tools out there. Certainly what INFORMS is doing is terrific.
It’s important to keep your skills fresh and make sure you continue to learn. When it comes to giving general career advice, especially to younger candidates, my advice is this: prepare for three or four careers during your lifetime. In today’s world, it’s not good to specialize in one thing and try to stick with one company or one industry or one vertical application for your entire career. It’s incredibly dangerous, and it likely won’t carry you through a 35-year career. You need to be continuously learning something new. People should keep that in mind.
INFORMS offers an analytics certification program (CAP). Is that a differentiator in the job marketplace?
No two candidates are ever equal, but it can certainly help once there are enough employers out there who understand what it means to be CAP certified. I’m seeing people put various MOOCs (massively open online course) on their resumes now, along with Kaggle competition results. I have a candidate who actually got his job because of a Kaggle competition. The first couple of times he submitted his solution it was totally
rejected, but as he continued to study the problem and resubmitted, he climbed up the leaderboard. Then he started getting calls and job opportunities because of his Kaggle rank.
From your perspective, what does the future hold for data scientists and other analytics professionals?
In my 30 years of experience, I have never seen anything like this. The opportunities for elite analytics candidates have never been better, and I think what we’re seeing now is just the tip of the iceberg.
As I said earlier, I really think that my quantitative candidates are going to be running companies one day. Certainly the CMO (chief marketing officer) is going to be coming up through the analytics ranks. Now there’s all this talk about CAOs (chief analytics officer). I think the candidates I’m working with have a very strong chance – if they have leadership ability and the ambition – to advance up the ranks and continue to climb and run organizations at some point. Their quantitative skills are going to be unique and absolutely required to be a successful businessperson. It’s their time to shine.
Peter Horner (email@example.com) is the editor of Analytics and OR/MS Today magazines.
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