Mind The Gap: Minting New Data Science and Analytics Professionals


Estimates today vary on the gap between business needs and qualified people with the data skills that are so in demand. But it is clear that this is one field in which demand exceeds the supply.

A Datanami article looked at various estimates about how many more data scientists from firms like Gartner and McKinsey to arrive at a range of 100,000-190,000 shortfall by 2020 and 2017, respectively. That's about 60% more demand than available supply in the US. The upside is that salaries for those jobs go up, but the downside, of course, is that the businesses cannot progress on the data front as much as they would like to without the skilled people in-house.

The obvious solution to that problem is to get more people qualified for these jobs. If they didn't learn the skills in college programs, they can now get trained in specialty programs like the NYC Data Science Academy (NYCDSA). Vivian Zhang, the CTO of the school, set it up specifically to meet industry needs and get people the data science training needed to fill those open job slots.

In a phone conversation, Zhang  declared, "I really love data science." While doing her graduate work in computer science, she decided that she also wanted to pursue statistics and so she got a double degree with a Masters of Applied Mathematics and Statistics as well as the MS in Computer Science. She worked as a Senior Analyst and Biostatistician at Memorial Sloan-Kettering Cancer Center and Scientific Programmer at Brown University. She has also taught outside the university setting, and when companies like Mckinsey and Microsoft started sponsoring her meetups, her corporate orders grew. Then she recognized "a big trend is that every company wants to become data smart," and that a school that could provide it was needed.

(Image: GUNDAM_Ai/Shutterstock)

(Image: GUNDAM_Ai/Shutterstock)

She originally registered the school's program in November 2013 and found its revenue increased 10 times over just three years.

"They come to us because they recognize that we're the leaders in this," she said. The demand comes primarily from companies that approach the school for team training, which accounts for about 60% of the students. The remaining 40% are individuals who have decided to hone their skills on their own. For the latter, the school boasts that over 90% land a job within six months of graduation.

The key to the graduates' success is the instructors' market experience and practical training for the students. "Our education is very hand-on," Zhang explains. Students who complete the training build a portfolio. As a result, they have something to show to prospective employers that demonstrates what they can do with data. Examples of student projects can be seen here: http://blog.nycdatascience.com/category/student-works/

The school, which is licensed by the US Department of Education, has are more than 1,000 part-time students registered for its certificate program. Some come to physical classrooms in New York, though they have an option to attend online training from anywhere in the world. The school offers 4,560 hours of recorded training content.

Capitalizing on that resource, the school recently launched its Remote Data Science Bootcamp, which covers everything from basic programming and data analysis with R and Python to machine learning and big data techniques. As a full-time program it takes 12 weeks to complete. For those who have to work while taking the course, there are a number of part-time or flexible options to enable them to complete the program in four, six, or ten months.

In addition to the training provided by the school, the organization behind the school, Supstat, offers consulting services. Zhang estimates that 90% of the people "know the domain very well" and come to them for advice on question like whether they should keep their data on the premises or go to the cloud. The other "10% say they know nothing and that's why they come to us" to get them set up from ground zero. They don’t just give them a list to work off of to complete their training. Zhang explains that too many things can go wrong that way, so they "stay on with them to make sure onboarding" and everything else is working properly.

Ariella Brown,

Ariella Brown is a social media consultant, editor, and freelance writer who frequently writes about the application of technology to business. She holds a PhD in English from the City University of New York. Her Twitter handle is @AriellaBrown.

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Re: Data Science programs
  • 1/31/2017 9:19:35 AM
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the real benefit to [an MBA] program wasn't necessarily the classes, but the chance to network with fellow students.

@Broadway - I wonder if the professor who said this ever thought about how much Networking an inventive student could do with $50K per year?

 

Re: Data Science programs
  • 1/30/2017 11:37:40 PM
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Ariella, no doubt we learn more on the job than at school. And leaves you to wonder what we can learn from professors at schools who never ever worked in the "real world." I recently heard a story from a student at an MBA program where a professor told her that the real benefit to program wasn;t necessarily his or anybody's classes, but the chance to network with fellow students.

Re: Data Science programs
  • 1/30/2017 12:23:38 PM
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Good idea, although the next question becomes how many people are in school and are they enough to make headway against the gap. I am thinking not in some instances.

Re: Data Science programs
  • 1/30/2017 12:21:39 PM
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I also worry about the cost of education, if the personal ROI from it is now out of balance.  Cuts would go a long way.

Re: Data Science programs
  • 1/7/2017 4:47:20 PM
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Lowering education fees and associated costs should go a long way toward alleviating the as mentioned "100,000-190,000 shortfall by 2020 and 2017, respectively." With the demand growing as employers wanting to shorten their costs in hiring qualified professionals, there would seem to be a real need to get more folks into the pipeline sooner rather than later.

Re: Data Science programs
  • 1/5/2017 11:57:48 AM
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Mentors from outside industries would certainly be helpful - aids innovation for having perspective beyond the technical aspects of data science.

Re: Data Science programs
  • 1/1/2017 12:40:56 AM
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@Broadway the oral exams are a cake walk compared to the dissertation defense! I speak from experience. For regular careers, you have a type of oral exam at any interview in which you have to prove your technical knowledge on the spot.

Re: Data Science programs
  • 1/1/2017 12:38:41 AM
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@terry I currently have kids in college and do get into this discussion. One is inclined to just go on to graduate school straight, but I tell her that certain programs -- certainly for MBAs and the like -- want to see some relevant work experience and even assume that you'd be working while pursuing the degree. So I've been trying to direct her to pursue what she can in terms of internships to improve her chances going forward. I've also told her to speak to people in various fields, and some have pointed out that they have learned a lot more on the job than in school.

Re: Data Science programs
  • 1/1/2017 12:35:24 AM
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@rbaz yes, in fact, the only majors that lead directly to a career are accounting, computer science, engineering, and math -- for acutaries. Everything else is just considered a general degree that can perhaps preprare you for graduate study in the same field (i.e. economics, sociology, history, English, etc.) but not qualify you directly for a job. 

Re: Data Science programs
  • 12/31/2016 5:49:33 PM
NO RATINGS

Get these grad students in real world internships for a semester or two. Get them mentors with industry professionals and or professors with real world experience. Save the oral examinations for the Ph.D. Students.

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