No employment friendly courses in data science

The drought can be attributed to the lack of industry-oriented educational and training programmes and employment-friendly data science courses

Gaurav Vohra

Data science may be the ‘sexiest job of the 21st century’ but the data analytics talent pool continues to remain shallow. A Mckinsey report bemoaned the fact that, “The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.”

A Wall Street Journal study in turn revealed that “80% of new data scientist jobs created between 2010 and 2011 has not been filled!”

It would seem that the data science scene in India is equally hamstrung. At the Big Data and Analytics Summit of 2014, Srikanth Velamakkani, the CEO of Fractal, was quoted as saying that, “Presently, there are only 10,000-15,000 analytics and data experts in the country, and there will be a shortage of two lakh data scientists in the country over the next few years.”

As the Mckinsey quote at the top of the article points out, there are two underrepresented categories of data scientist across major industry verticals: certified analysts and non-data science professionals with a good command of data science tools and techniques that allow them “to understand and make [timely business] decisions”. Given that the current shortage is only expected to grow more extreme, let’s examine some of its key drivers.

Why the talent-tap is running dry

The ‘global talent drought’ of professionals with data science skills can be attributed in large part to a lack of industry-oriented educational and training programmes, and employment-friendly data science courses.

A lack of targeted options

To begin with, let’s take a look at the situation in the US and globally to assess the scope of this problem. While the number of universities offering data science courses in the US is on the rise, the majority of them are master’s programmes.

On the global stage, universities in Australia and New Zealand are incorporating data science courses and degrees into their curricula at the bachelor’s and the master’s levels. While this is a promising set of developments, it continues to be an inadequate response to the ‘talent drought’ facing the world’s major economies. Here are two reasons:

1. A bachelor’s degree in business analytics is only of use to students who know, at an early age, that they want a career in business analytics. This is therefore a very narrow point of entry into the field and cannot produce data scientists at the rate at which they are required.

2. Master’s degrees come with their own challenges. For one thing, they consume a whole year or two’s worth of time and money—an investment that professionals looking to acquire or strengthen specific data science skill sets may not be able or willing to make.

Workable alternatives

In a fascinating LinkedIn post entitled “Why I Left My Data Science Master's Program”, Charles Pensig, a researcher at Optimizely -- a company that provides organisations with the tools they need to optimise their websites and mobile apps so that they can offer “highly relevant digital experiences to their customers” -- explains his decision to leave the programme thus:

“I have a great idea of what I need to learn to be where I want to be in 10 years. Doing this [the MA] was less a matter of exploring than learning what I need to in the fastest way possible.

Since a full-fledged MA wasn’t the best way to learn what he needed either efficiently or quickly, Charles took another route. What he did, and encourages other professionals like him to do, is ‘Sign up for some online classes, get a pile of books, schedule two hours into every week night, and sit at an empty desk working through them. Don't leave the desk.’”

Elaborating on his decision to take virtual classes, Charles writes, “I chose to leave the (master’s) programme because I knew my free time could be better used if managed at my own pace.” Furthermore, “By self-pacing, I'm getting through about 1.5x the academic content I previously was.”

Viable alternatives

There are many professionals like Charles the world over, and in India as well. Online courses in data science that target specific industries and verticals, and that equip learners with a highly customised but varied skill set would seem to be the most pragmatic solution to the deficit in data scientists. They provide them with a blend of data science theory and practice that is industry-specific as well as hands-on.

Time and (the information) tide wait for no one. The sooner we start addressing this talent deficit, the better.

Souce: techgig.com