What makes a data scientist?

It's a whole new ballgame for traditional data analysts, as training focuses on deep knowledge of statistics and computer science.

Universities Step Up

The skills required to perform these tasks cut across traditional academic disciplines, including statistics, mathematics and computer science. This is why several US institutions, including New York University and NC State, offer specialised data scientist certification and degree programs.

"Data used to be something you collected. It had neat rows and columns," explains Rappa. "You ran experiments that were time-consuming, laborious and costly, and you didn't have a lot of data so you dealt with sample sizes."

Now, in contrast, " data comes streaming off of every touch point you have with employees, partners and customers," he says. "Big data is about taking all of that data together and using it to optimise business or inventory levels or to better target customers. That's the trick of the whole thing. You need people who are good at handling large volumes of data and have knowledge of math and statistics to analyse the data."

Recognising this as early as 2005, NC State created the Institute for Advanced Analytics, which pulls together faculty members from various disciplines and teaches data science "in a very integrated way," Rappa says. Students take technical courses in statistics, finance and business, and they learn communications and teamwork skills, which Rappa says "almost always trump the technical skills," as far as employers are concerned.

Teamwork skills are critical, he says, because "you can't wrap up all of the [data scientist] skills you need in a single person." (See " Stalking the Elusive Data Scientist.") Instead, data scientists typically work in teams. IBM, for example, mixes statisticians with MBAs in its Data Analytics Center of Excellence, which helps businesspeople determine what questions they need data to answer. The centre's goal is to generate revenue through a marriage of business savvy and analytics, says CIO Jeanette Horan. One project optimised sales coverage in the 170 countries in which IBM operates, yielding a 10 per cent performance improvement in territories where the models were applied.

Rather than completing a final thesis, students work in teams to complete practicum projects with live data from major companies, including GE and GlaxoSmithKline. Seventy per cent of the program's students come from the workforce, many of them sponsored by their employers. Most students have at least two years of on-the-job experience, and their average age is 29.

At NYU, the newly launched, two-year master of data science degree is also multidisciplinary, intersecting mathematics, computer science and statistics. This is because to do data science well, "you need to have expertise in all three," says Roy Lowrance, managing director of the university's Center for Data Science.

Lowrance emphasises that data scientists also require what he calls "application knowledge." Without it, "you have no intuition about what to work on and test, especially in business," he explains.

What Lowrance refers to as application knowledge, some other experts describe as domain expertise. But whatever you call it, all agree that it's absolutely essential for data scientists in the business world.

Because data scientists are charged ultimately with showing business value, knowing a particular business is critical "because there's a lot of nuance in each domain", says Josh Williams, a data scientist at Kontagent, a company that finds and identifies customer behavioural insights from social, mobile and Web data in real time.

"A data scientist is someone who is familiar with statistics and classical mathematical analysis, and they need a strong background in programming and computer science or at least the ability to get things done in a programming language," Williams says. "But they also need domain expertise around how to apply different automated analysis algorithms to a given domain."

However, he adds, "data science skills are not necessarily industry-transferrable" because the volume and complexity of data varies from industry to industry. "We're dealing with orders-of-magnitude greater volumes, but the really important part is that the data is much more rich and complex," Williams says.

Follow CMO on Twitter: @CMOAustralia or take part in the CMO Australia conversation on LinkedIn: CMO Australia.

Join the newsletter!


Sign up to gain exclusive access to email subscriptions, event invitations, competitions, giveaways, and much more.

Membership is free, and your security and privacy remain protected. View our privacy policy before signing up.

Error: Please check your email address.
Show Comments

Blog Posts

Channelling climate positive design

As we enter 2020, the new decade spells infinite possibility in digital and design. Yet ironically, the biggest trend we’re facing has nothing to do to with innovative technology. It is something much more ‘down to earth’: The state of our planet. Or more specifically: Climate change.

Katja Forbes

Founder and chief, sfyte

Non-linear transformation: The internal struggle

Let’s face it, transformation is messy. Every business is different, with a set of specific challenges based on a mixture of external (the market, competitors, regulation) and internal factors (technology, people and process investments over time).

Neil Kelly

Partner, transformation, Wunderman Thompson

7 ways to champion a human centred design culture

Human Centred Design (HCD) has come a long way in the last decade with many forward-thinking organisations now asking for HCD teams on their projects. It’s increasingly seen as essential to unlocking innovation, driving superior customer experiences and reducing delivery risk.

Shane Burford

Head of research and design, RXP Group

If you want to know how to compose a thesis for a research paper correctly, you may visit a page from my profile. Here you can find a det...

Emily Walsh

Why negative messaging isn’t working for your brand

Read more

Nice to read the post. A good leader and an effective recruitment in top level is a must for smooth running business. Congrats..

Wollermann Business Brokers

Aus Post recruits tasks new CMO with building modern iconic brand

Read more

I think some of these ideas are great. These tips will help me to improve my system. Thanks!

Henry Reid

9 Ways to Improve Your Company's CRM System

Read more

It's a useful info for small businesses owners. We can't live without mobile apps. They are so helpful! It's hard to deny that.

Mae Davis

7 ways small businesses can benefit from mobile apps

Read more

Hi Jennifer,Fascinating read about design-led companies!If you would like to learn more, our Design Thinking and Innovation programme mig...

Andrea Foster

How to spot a ‘design-led’ versus ‘design-fed’ company

Read more

Latest Podcast

More podcasts

Sign in