Since 2015, more than 240 analysts from 90 organisations have completed the Data Science Accelerator mentoring programme. Applications are now open for the programme’s 18th cohort, and its longevity highlights what a fantastic opportunity it brings for UK public sector analysts to develop data science skills and apply them to challenging problems in their organisations.
The programme normally facilitates face-to-face mentoring delivered at regional hubs, however the coronavirus pandemic meant that the programme switched to remote delivery in 2020. Despite these challenges, 50 mentees successfully completed the programme last year.
We caught up with 3 graduates from the latest Accelerator cohort. They spoke about why they chose the Accelerator, how the programe helped them, their experiences of being mentored remotely, and gave advice to others considering applying.
Ben Parnell, Lead Analyst, Metropolitan Police
I saw the advert for the Data Science Accelerator programme when the Met was focusing on developing these capabilities. I knew it was the perfect time to apply after a long-term interest in data science.
I was attracted by the range of projects previous participants had worked on. Although I was initially apprehensive about how steep the learning curve would be, there was extensive support available from the mentors, programme staff and the cross-government data science community.
I’ve learned how to code in Python and implement various code libraries. I also created a set of tuned machine learning models to classify different crime types based on free-text information – the main objective of my project. I now have the confidence to develop this further, beyond the programme.
I’d advise new mentees to do some form of coding training before the programme to understand the basics of your chosen language, such as data types and their manipulation, syntax, and troubleshooting coding errors. There are loads of resources online to help. This will help you hit the ground running on day one.
Also, make sure you can protect your project time each week. Although working flexibly brought its own benefits, it made avoiding other work and home distractions more challenging.
Do it, tell everyone you’re doing it, and then tell them what you’ve managed to do this week, which you couldn’t do the week before. They’ll be really interested and having an engaged audience helps keep the momentum going.
Anne Griffith, Higher Statistical Officer, Office for National Statistics
As soon as I heard about the Data Science Accelerator, I knew I wanted to apply. My role included a fair amount of work in Python; however, I was keen to develop my knowledge and skills after a long career break.
I began in Autumn 2020 when home-working was the new normal, so mentoring via video conferencing software did not feel like a hindrance - in fact sharing screens is a useful way to look at code together. I also took part in weekly stand-ups with small groups from across government departments, hearing about their data science projects. I had no idea so many departments had data scientists working in them!
I had 2 mentors who were excellent and very knowledgeable. They made sure I had the resources I needed and planned ahead to ensure we had a working product at the end of the project. The scheme has helped me develop new skills that I am already applying in my daily work.
My coding skills have definitely improved and I learnt a lot about best practice, such as organising a complex project to a fairly tight schedule and I now have a general understanding of natural language processing (NLP) techniques, which is a fascinating area. I would definitely encourage anyone who wants to improve their data science knowledge and skills to apply, it will benefit both you and your organisation.
Jutka Molnar Sansum, Software Developer, HM Land Registry
I have been interested in data science for a long time. When I started to work for HM Land Registry (HMLR), my colleagues saw my long-term enthusiasm for data science and told me about the Accelerator programme. I work with very large datasets and there are many scenarios where data science would help to deal with these efficiently. The programme gave me the opportunity to learn more about data science through trying to solve real problems for my organisation.
An experienced data scientist helps you learn about data science methods and good practices. For example, they help you to organise your work, your code, and use of annotations. This will help you when you revisit your work later or make it understandable for others to look at.
Setting up a Git-connection was challenging because my mentor could not have access to our organisation’s GitLab site. This was difficult for me because I was new to git but it was very useful to use these new skills to share my code with my mentor.
Make sure that your data is ready to use. Think in advance about what and how you can share with your mentor, and set up sharing protocols before the project starts. This will allow you to focus valuable time on the data science part of your project so that you can achieve the best out of the 12 days allotted.
Information for prospective applicants
Over a period of 12 weeks, participants will:
- spend one day per week working on a data science project that tackles a business problem
- receive remote mentoring support from an experienced data scientist
This forms your protected learning and development time, ensuring that you have the opportunity to develop your skills.
How do we choose participants?
The most important things we look for are well-considered and interesting project ideas, enthusiasm to try new things, and dedication to the programme. Your line manager and your Head of Profession (or equivalent) must agree that your project tackles a business problem with data that you have access to, and that you can commit to the time requirements. Coding experience is desirable but not essential.
Examples of previous projects can be found on the Data in Government blog. We will also be running a project clinic led by past mentors on 28 January who can help you decide if the programme is for you. To register your interest, please email the Data Science Accelerator team.
How do I apply?
Visit the Data Science Accelerator programme page to apply by Friday, 12 February. The induction will be held week commencing 29 March and project work will start on Thursday, 8 April.
Can’t make these dates?
The cohort following this one will take place in the second half of 2021. Applications will open in June and projects will take place between August and November. To keep up to date with the programme and future cohorts, please sign up to the Government Data Science Partnership mailing list.
For more information, please email the Data Science Accelerator team.