Civil Service Internship
Many months ago I was looking at the civil service jobs site and saw the Government Statistical Service’s student internship opportunity. I jumped at the chance to apply. My degree involves not only data science and statistics but also a heavy focus on social issues and public policy. I’ve often done assignments on ONS and Census data so working in the civil service is something that I increasingly became more interested in. The application process involved submitting a personal statement and excerpts from a CV and then undergoing an interview on the civil service success profiles and behaviours. I got accepted earlier on in the year but when COVID hit these plans were thrown into uncertainty. But around April I got a very welcomed email saying I had been found a position and they were interested in doing it remotely.
I was placed within the Cabinet Office, in a team called Constitution Group Analysis — the analysis arm of Constitution Group within the Cabinet Office. As my internship was an incredibly short 4 weeks — due to me starting at the BBC in August — I worked on 1 main project throughout my time. I’m not sure how much detail I can give so I’ll err on the side of caution. Before I began I met my manager in Whitehall for an induction and general intro. My start date also coincided with Civil Service Live: a festival of talks from across government. I got to hear from many civil servants giving their insights on topics ranging from data to the environment.
In essence my task was to perform an exploratory data analysis and feedback my insights. My line manager was particularly keen for me to look at this work as it had been on the backburner for a while and my R skills would come in handy. I set to work at loading the data into R and creating some simple visualisations using ggplot. It started out very broad, I would visualise anything and everything and discuss my findings with my manager who in turn gave me lots of R tips and direction. Clarity came when we met with a policy colleague who had some thoughts on what the data may show. This led to a focus on the regional aspect of the data — I was to focus on creating visualisations and descriptive statistics to highlight any regional trends and outliers.
For the next 4 weeks I created countless scatter plots, box plots, heat maps, calculated many statistics and ploughed away in R Studio. The process was both hard and simple, simple because I was very familiar with R beforehand but challenging because unlike my previous university assignments this work was on a real unedited dataset. I encountered many data issues that I was not used to, I came across many techniques I was not able to do. This is where a special thanks must go to my amazing line manager. She helped me improve my coding such much and made it so easy and comfortable to ask her for help. Despite a busy schedule she was always on hand to help — even outside of our 3 weekly meetings. I’ve never had a manager who has supported me and challenged me to this extent and I will always be grateful. She also gave me the tools to properly scope out and plan the project effectively. Laying out my objectives for the internship and project early on added a lot of structure and organisation that helped me thrive.
In the end I uncovered many location focussed insights that had not been shown before. I created a presentation using R markdown and embedded plotly charts to make it interactive and dynamic. I presented, virtually, to the rest of my analysis team and also to a few select policy colleagues. A G6 policy civil servant was so impressed and informed by my insights he couldn’t help but exclaim that he couldn’t wait to get his hands on my slide pack. The presentation was one of my proudest moments, only days before it was confused, unfinished and convoluted but by the end I had managed to deliver a clear, well informed piece of analysis.
Aside from my project I also took the opportunity to attend talks on analysis conducted by staff within the Cabinet Office and further afield. It was really fascinating to see how data is used by civil servants and the kind of projects they work on. This put into perspective my studies and also got me very excited about a future career in government.
All in all I learned a lot of new R techniques and most importantly got a great insight into the civil service. I’m incredibly proud of all that I managed to achieve in only 4 weeks. The experience has made me quite motivated to begin my working career in the civil service — using data to make a difference.
