This is a profile from the 2022 version of the DataIQ 100.
The latest list is available here.
What has been your career path to date?
I left academia after completing my PhD in Random Matrix Theory and spent the next year volunteering at FareShare in Bristol and travelling around South East Asia. Shortly after returning, I joined the Civil Service as an operational researcher. I was at home here - being part of a bigger organisation and working on technical problems to serve a sort of common good felt quite similar to working in academia and the problem space was interesting.
I started getting itchy feet when I learnt more about data science and the different tools and techniques other companies were using to solve similar data problems. At least at that time, I wasn’t able to bring these tools and techniques into my role. So I left the Civil Service to join the Faculty fellowship program in 2016 and get more practical experience working as a data scientist. As part of this fellowship, I did a project with tails.com and I’ve been there ever since.
While the core values and company culture at tails.com has remained unchanged, the company today looks different to the small start-up I originally joined. As the company has grown, the needs for data and data science and the scope of my role have changed with it.
What made you choose data as your career focus?
What I enjoyed most from my PhD and from mathematics in general was the nature of problem solving - breaking something down, looking at something from different angles and finding clarity and understanding. But what I felt I was missing from academia is the opportunity actually to have practical impact with my work. So I chose to work in data to keep this technical problem-solving part of my job, while being able to have real impact. Looking back, I know I made the right choice.
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