Analytics Magazine Analytics Magazine, July/August 2014 | Page 56

Q&A W ITH LI NDA B U R TC H or target marketing. More recently I’ve gotten into data science. That’s a huge umbrella description. 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 unYou mentioned operations research, structured. It’s something that’s going to the heart and soul of INFORMS. grow as sensors become more and more It is. When I started out in recruit- prevalent and data streams become coning more than 30 years ago, I focused tinuous in so many applications areas. on operations research candidates. It’s grown pretty dramatically since then. How would you describe the current They have a very fond place in my heart job market for quants, for lack of a because that’s how I got started. It’s one better word? of those things that I’ve really been inIt’s hot. A couple of months ago we did volved with – the INFORMS group back a flash survey in which we simply asked in New York when I was living there, how often are you are contacted about a and I’m really excited now because the new job opportunity through LinkedIn. We INFORMS group in Chicago is getting had 400 responses; 89 percent of the rere-energized. It’s really exciting to watch. spondents said they were contacted at least monthly, and 25 percent said that they When looking at the job market- were contacted at least weekly. I’m working place, do you distinguish between, with elite data scientists, and they’re telling say, a data scientist and other analyt- me that they get calls once or twice a day ics professionals? from recruiters, so it’s just crazy. Let me back up a little bit. Last sumOur candidates are seeing a 14 permer, when I was putting together the big cent increase in salary when they change data salary study, I saw that data scien- jobs, so there’s a lot of churn out there. tists were a breed apart, and that they If they stay with their existing company, had higher compensation levels. So I they might see an annual increase of bemade the decision to take them out of the tween 2 percent and 3 percent, so the general big data study and hold them for 14 percent is a nice bounce if they delater because it’s such an emerging field cide to make a change. One of my data that’s so different. They are working with scientists in Boston said he received 30 what I would call unstructured data. You calls in one week after he left a job and could get into a lot more detail over how a went on the job hunt. 56 | A N A LY T I C S - M A G A Z I N E . O R G W W W. I N F O R M S . O R G