Chris Storey is a student in the capital who has just completed the final module of his post-graduate course in spatial data science at a London university. His aim is to get a job as a data scientist in a logistics, planning or big retail company where he will be able to answer “spatial questions.” We met at a data event and I was keen to understand his motivation and goals for working with data.
"Spatial analytics is a niche to bring to any data science analytics role."
During the post-graduate course, Storey was trained in the theory and techniques of data science, visualisation, GIS (geographic information systems) and virtual environments, with a focus on analysis and mapping. “Spatial analytics is really important to me and a bit of a niche to bring to any kind of data science analytics role. I’d be really interested in working in companies that answer spatial questions like, 'where do things need to go?' and, 'how do things move around these spaces?',” he said.
When assessing possible places of study, Storey considered the University of Edinburgh and Newcastle University, which is part-funding the construction of a National Innovation Centre for Data, but ultimately decided to study at UCL.
The decision to go into the niche area of spatial analytics was the result of his background in geography. While studying the subject at undergraduate level, he developed a strong interest in GIS modelling, and even did a GIS modelling project for his dissertation. Storey's second job after university was at a GIS software development company where he picked up an understanding of coding, especially Python.
However, most of his time was spent in a technical customer support role, where he would help troubleshoot customers’ issues over the phone. Although he enjoyed the calls, in which he gave advice on how to do a particular action or get to a particular result, he began to feel constrained.
"I needed to do some extra education to fill the gaps."
“It got a bit frustrating because you can do all these quite cool and exciting things with people on the phone, but they were never your project and you never got to see any of them through,” Storey said. “I needed to do some extra education to fill the gaps to get to where I wanted to be, in a role where you are taking on projects and answering questions for people.”
He decided to move on but found it impossible to get a job as a the kind of job he wanted - an analytical role - without extending his skills. He said: “I didn’t have enough experience in statistics and a proper grounding in core coding.”
That changed at the very beginning of the course, with the students having to learn three languages – Processing, R and Python – simultaneously. “It was used to get everyone up to speed on the idea of code structure. It was a good balance, but it was a lot to take in.”
"People from all sorts of fields came together on the course."
The most surprising thing for him was seeing the wide appeal of data science to people from across a gamut of industries. He said: “There was a real variety of backgrounds of everyone on the course. There seemed to be people from all sorts of fields coming together with a similar interest in this thing.”
Upon reflection, he said that it made sense that spatial data science would have wide appeal because it draws on so many disciplines. These include cartography, computer science, environmental science, geography and planning, among others.
To make the transition from student to professional, for the past few months his classmates have been reaching out to companies to forge working relationships. There were was also support from the university which hosted weekly lectures where academics and data industry professionals were invited to speak to the students. He said that at these events, he and his peers were encouraged to connect with representatives of companies that were looking to hire. The lecturers also sent around details of open vacancies and research positions across the world. “People have a lot of connections all over the place, which is really cool,” he said.
"I can take a data set and quickly dive in with tools."
Having completed the course, Storey is pleased with the way he has upskilled himself in terms of data. He said: “I’m really enjoying being quite competent in being given a data set and being able quite quickly to dive in with some tools and gain some understanding about it.” He added that ,while data sets can be quite messy and poorly structured, he is no longer daunted by this and now enjoys the confidence of being able to use the tools at his disposal to draw insight from them.
Much has been said of the data skills shortage in the UK, and the British education system has been criticised at secondary and tertiary level for failing to equip the next generation of data professionals with the skills needed. However, with awareness and the appeal of the data science industry growing, there are some green shoots coming through in the field of UK talent, Storey being one of them.