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.

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.