What do data scientists want from work?

NITECH ››› DEVELOPING CAREERS IN DATA SCIENCE

WHAT DO DATA SCIENTISTS

WANT FROM WORK?

108 Simon Michell talks to Iván Ortega, Director of Amsterdam’s Innovation Hub for Data Science and Artificial Intelligence, to find out more about this new cohort of data scientists and what they desire from their careers

Amsterdam Science Park

Some data scientists are seen by many as latterday alchemists – white knights that ride to the rescue bearing a secret potion capable of solving all the world’s problems. And, to tell the truth, many do seem to see themselves as ‘stormtroopers’, cast in the same mould as Navy Seals or elite Olympic athletes.

It is not surprising then that this mythical status is attracting a lot of attention. “Data science is trending. It is a buzz, especially if you come from California where I’m from,” says Iván Ortega. “Young, or recently graduated, data scientists like to think of themselves as hotshots.” He should know – as Director of the Innovation Hub for Data Science and Artificial Intelligence located at the Amsterdam Science Park’s Startup Village, he is surrounded by them and makes a living from recruiting them for his projects.

A RARE COMMODITY

This recent data science phenomenon is attracting huge numbers of STEM (science, technology, engineering and mathematics) students across the world, but especially in NATO’s back yard – Europe and North America. You would think there would be a buyers’ market where those who wanted to recruit data scientists had their pick of the bunch.

Nothing could be further from the truth, as Ortega explains. “If you take a close look at the pool of 109

110 available data science graduates that an organization like the NCI Agency might be able to recruit, you will probably find that roughly a quarter of them will want to go off and create their own businesses – become entrepreneurs. Of the remainder, particularly those who already have or are taking Masters’ degrees and Doctorates, at least 50% of them are international students from non-NATO countries – China, India, Iran, Pakistan etc.”

For NATO, and many other ‘transatlantic’ organizations in both the public and private sectors with more rigorous recruitment requirements than many, this makes the available group of data scientists approximately a third of the whole community. Even before you start looking for recruits, just under 70% or so are already beyond reach. That is before big hitters such as Amazon, Apple and Google swoop in and take what they need.

Ortega highlights the challenge. “I have been asked by the NCI Agency to find a pair of interns for them,” he says. “There has been a very large and enthusiastic response, but when I go through the CVs, more than two-thirds are from applicants outside of NATO Member States. Attracting candidates is hard – retaining them is even harder. Why? Because they want to work on the coolest projects. They want to cure illnesses. They want to stop climate change. They want to save the world!”

Money is a factor, but not the only one. According to Ortega, potential recruits will want to know who else works for their prospective employer, who will mentor them and who they are going to be working with. Fundamentally, data scientists want to know what kind of cool projects they will be working on.

“Data scientists can be very competitive. They want bragging rights and street cred”

With such a dearth of available talent, there is, without doubt, a pool of data scientists that is not being fully exploited – women. Ortega thinks this may be because most recruiters are male. “As the saying goes, ‘it takes women to recruit women’,” he says. The emergence of groups like Women in AI and Women in Tech is a concrete indication that female data scientists want equal representation and a fairer recruiting system.

Ortega admits that there is still quite a gender imbalance in data science, but that things are changing, with groups springing up to offer support to women who have become or want to become data scientists. He cites among others the mentorship group known as PyLadies, and the R-Ladies, an organization promoting gender diversity in the ‘R community’, that is to say the statistics and data science community. Ortega points out that, whatever their gender or background, “Data scientists can be very competitive. They want bragging rights and street cred”.

DATA SCIENTISTS WORKING WITH THE NCI AGENCY

Iván Ortega recently worked with the NCI Agency to assess civil standards for data science, bringing both industry and academic experience to the task. To fulfil the task, he has recruited data scientists from the hub, including from its founding company, Qualogy, as well as a small group from their partners at S&T (Science & Technology) to help him.

What they are trying to do is create a profile of standards and best practice for artificial intelligence that NATO can use going forward. Standards are important to NATO, as they allow systems to interoperate. But the benefits of interoperability sometimes come at the cost of flexibility.

“My NATO oversight, Michael Street, who is Head of Data Science and AI at the NCI Agency, asked us to find the best data science standards being developed by civilian standards bodies, implement them into an interoperability simulation model, and then assess which really bring value to data science scenarios.

The aim was to inform NATO on which civil standards, if any, should be adopted as official standards that NATO can abide by and use in order to get the benefits of interoperability and innovation as data science evolves across the Alliance.”