Industry Insights

Background image of user typing on a calculator with floating interface elements surrounding them

Burtch Works' Predictions - 2015 Analytics and Data Science Hiring Market

January 12, 2015

Linda Burtch, Managing Director at Burtch Works | 30+ years’ experience in quantitative recruitingWhen I wrote my predictions for 2014 I wrote that thanks to Big Data, analytics has become inescapable, and looking now into 2015, I believe that statement more than ever.


It’s not just analytics in the public eye either – data science has been thrust into the spotlight, and the hiring market for analytics professionals and data scientists has gone into overdrive. Despite salary increases companies are still struggling to hire, and talented professionals are going on and off the market almost faster than you can snap your fingers. While it is still crucial to keep your job search skills sharp, there has never been a better time to be a Quant looking for a job.So what does all of this excitement mean for next year? I have a few predictions:

  1. Forget the C-Suite if you’re not a Data Geek – Maybe not for next year, but that is the direction that business is going. The complexity of managing any large organization effectively has escalated dramatically, and success in the future is going to depend on how “Big Data” savvy any C-level leader is.
  1. Traditional Fortune 100 firms board the data science bandwagon – With the data science trend gaining momentum, I predict that legacy firms will build up their data science teams. Whereas last year there was still some confusion and hesitation, this year will see more investment, and a plan of attack for hiring. The amount of calls I’ve received from companies asking questions has risen substantially, and I anticipate it will continue long into 2015. From tech firms like Google, LinkedIn, Amazon, or Uber, to legacy firms like the Gap, Zurich Insurance, General Motors, Clorox, and AIG, organizations in every industry are boarding the data science bandwagon.
  1. California loses its luster – Almost half of all data scientists, the elusive king-pins of the Big Data movement, are on the West Coast working for technology and gaming companies. But, cities in California account for nine out of the top ten cities with the highest average home prices in the US, and the rent is also very high. However, the biggest reason that I’m predicting the California craze dies down is that professionals will start to realize that there are plenty of high-paying jobs outside The Golden State that might offer more opportunities to make a measurable impact, advance their career, or to lead the Big Data initiative at their company rather than being “just another Quant” at one of the larger tech firms.
  1. Recruiting for startups gets harder – A few years into the startup bubble and the hype has just barely begun to subside, but I predict that next year startups’ ability to attract rockstar talent will diminish. Professionals will be less apt to blindly leap into a startup hoping for a lottery win as they see many of their colleagues bombing out.
  1. The lines blur between analytics and data science – As more predictive analytics professionals get accustomed to working with unstructured data, I believe there will be a natural evolution of analytics, with more analytics professionals picking up the skills necessary to work with the unstructured data that is common in data science. Want to know what it takes to be a data scientist? Here’s my list of essential data science skills that companies are all looking for.
  1. Bootcamps and MOOCs reign on – Companies hoping to address the talent gap are looking for a faster way to bring people up to speed, and professionals hoping to pick up new skills are looking for a quick primer. It remains to be seen how successful these programs will be in preparing their students, but they are a faster, cheaper way to transition as long as you have a strong quantitative foundation. Check out this post for more about these different learning approaches.
  1. Goodbye Hadoop, hello Spark! SAS, what’s that? – If Google is to be believed, then Hadoop is on its way out of the Big Data conversation. Aside from Hortonworks’ recent IPO, the buzz I’ve been hearing is all about Spark. Programming languages like R and Python are ubiquitous, and I believe that the future lies in open source tools; as always keeping your tools fresh is crucial to success in this quickly evolving field.
  1. Analytics salary bands get a lift – As our salary studies report, the average predictive analytics salary (non-managers) is $88.4k with a mean bonus of 11 percent, and for managers is $160k with a 19.1 percent bonus, and those paychecks are on the rise. Data scientist salaries are even higher, with the average (for non-managers) being $120k with a mean bonus of 14.5 percent and for managers $183k with a 19.5 percent bonus. Companies looking to recruit Big Data professionals will need to make sure their bands are competitive and think of other ways to lure talent, especially given the likelihood that they will be competing with multiple offers. For complete salary information for analytics professionals, data scientists, and marketing research professionals, you can download all of our salary studies here for free.

Interested to know how these changes may affect you? Check out my 2015 Predictions webinar recording on YouTube, where I go into more detail about each of my predictions, and offer advice for quantitative professionals at every level. Whether you're just starting out on your quantitative career, a seasoned veteran, or hiring analytics professionals and data scientists for your team, there's a little something for everybody working in and around the quantitative hiring market!Follow Burtch Works on Twitter or LinkedIn to get the best quantitative career news and blog updates delivered right to your news feed, and check out our YouTube channel for access to all our latest salary information and webinars!