By Dr Grace Kite

A career in data science

This is a talk that Grace gave to A-level students at Mulberry Academy, Shoreditch. It’s an ace school doing a phenomenal job for young people who often have some disadvantages. The idea was to open their horizons to different types of jobs and careers.

The start and end point of the story

Your teachers asked me to tell you a bit of my career story. How I got from where you are now to where I am now.

Hopefully it’s an interesting story.

The ending point of the story, i.e. the work I do now, is definitely an interesting place. I run a business which gives advice to companies, many of them you will have heard of – ASOS, Wagamama, ITV, Play Station, Hasbro, Heineken

The starting point of the story, when I was about your age, was 25 years ago. I read a science fiction book and in it the hero was trying to track down some bad guys, and he was doing it by following a trail of data that the bad guys had left behind. Transactions in restaurants, emails sent, an identifying piece of code buried in a video that went viral on the internet.

It totally captured my imagination. I thought wow.

If everywhere people go, they leave a trail of data….. Eventually that will build into a record of everything….. Everything that everyone thinks is important, and all the actions they take….. Summarised in data.

I wasn’t interested in chasing bad guys, I was interested in bigger questions:

– How does the world work?

– Why do people do the things that they do?

– If you want outcomes in the world to change, what should you do?

And I got really excited by the idea that you might be able to find answers to these questions by analysing this set of records, this massive lump of data we are all creating.

That curiosity about the world has never left me, and I’m still excited about answering questions using data and making better decisions because of it.

First thing that happened to get from start to end: data becomes available

Two things happened in the 25 years between now and then, which brought me to where I am now. The first is the fact that the science fiction turned into truth. More and more things that people did began to leave a data trail.

In 1994 when I was your age:

Most people didn’t have internet access, so there was no data on what people look at online, or what they buy

No-one had a smart phone so there was none of the kinds of data that your smart phone is collecting on you:

Who you call…. How long you talk for…. Where you go…. Which adverts you saw…. What you look at online…. All the photos you took and google backed up…. What you buy…..

So, there was huge change in the past 25 years brought about by technology. We got these hugely useful things called the internet and mobile phones and they set about collecting data. And every time there was new data or more data, people decided to analyse it.

What that meant was that there was a growing need for people like me who were curious about what you might learn looking at data. All kinds of companies needed people who could work with data.


Once I had some starter level skills I easily got a good job…. Once I had a good job, my employers trained me, and I got even better skills…. Then, when I had really good data analysis skills I started to get paid really well…. I was able to choose which questions I wanted to answer

Some of the recent questions I have answered – which I think are really interesting are:

– Why is ASOS so successful at selling clothes to young people? Should they make their clothes cheaper, or more expensive if they want to make more money?

– How many people will watch live TV on ITV in the future? Will Netflix and Amazon prime and YouTube eventually take over completely?

– Which Play Station games should they advertise on TV or on posters on the tube?

– If a beer company sponsors music gigs, will the people at the gig drink that beer? Will they continue to drink it after the event? How long for?

– The world has donated a huge amount of money to poor countries healthcare systems. Has that made people in those countries live longer? How much?

So, the first thing that helped my career to succeed was more and more data becoming available and so a growing need for people that can analyse data.

What was the second thing?

The second thing that happened to get from start to end: going to university

You don’t have to go to university to do data analysis. Some people learn on the job from scratch.

But what I did was study economics:

People think economics is all about money, but really it’s about patterns of behaviour. It’s full of little rules like if the situation is ….. we’d expect the outcome to be….

For example, if something becomes more expensive, we’ll buy less of it. Economics also has data analysis in it, because economists check that the little rules do turn out to be true in the real world by looking at data.

It gave me the skills to set out on my career knowing the best that there was to know at the time about finding real-world patterns in data. Lots of people will tell you they had loads of fun at university. That wasn’t really my experience, I had better friends here in London.

What I really valued at university was:

– Sharing ideas

– Meeting real people from different backgrounds and from abroad. I have kept in touch with many in India, the US, Canada and elsewhere.

– And of course, getting skills in something that was new – data analysis

So, to summarise, why was I able to have the success I’ve had

I worked hard at a-level and then went to uni to get the skills I needed to start out. It was something that I was interested in and excited about. I found a career in something that was new and growing – data analysis.

In this area there are always more jobs than people to do the jobs. That enabled me to progress quickly.

And the advice I would give to you is

– Yes work hard, and yes go to uni if you can

– Yes find something you’re really interested in

But also…. Have a think about what kind of people will be needed in the future? What human skills will complement the technologies of the NEXT 25 years.

In data, the newest technologies for analysing are AI and machine learning

And there are other new technologies that are interesting outside of data. Many people think blockchain is now what the internet was in 1994. There’s also layered reality, internet of things, and more. All good prospects for good progress in good careers.

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