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What did you enjoy most about your degree? 

One of the things I enjoyed most was learning about more innovative and complex statistical methods, from Bayesian inference to principal component analysis. Despite around 20% of my undergraduate mathematics degree being statistics and probability, it was only when I studied statistics as a postgraduate that I developed a real passion for it.

What are you doing now and how did you get into that role? 

After successfully completing the Civil Service Statistical Fast Stream scheme in summer 2021, I am about to start a role where I will have the opportunity to lead a team delivering statistical projects in a Government department. 

The Statistical Fast Stream scheme is a four-year leadership development scheme that gives participants a variety of postings designed to develop your strengths and better understand how government works. Whilst on the Fast Stream, I worked in a total of four different government departments. This included six months in a policy strategy team scoping out policy proposals for ministers, as well as in a refugee charity Breaking Barriers leading on their impact evaluation strategy.

Crucially, I learnt how to explain statistics to non-analysts, applying analysis to real-world situations. Sometimes this is not done by carrying out actual analysis but through planning an approach, conveying any limitations, and helping policy advisors to interpret data so they can make more informed decisions.

Government statistics has become an important part of the coronavirus pandemic response, adapting what they collect and publishing at pace to respond to this new environment. The country and the world are changing. Effective statistical analysis is crucial and will underpin government strategy in many areas.

What did you do for your MSc project? 

The ZAMSTAR (Zambia-South Africa TB and AIDS Reduction) community randomised trial was one of the largest-scale trials ever focusing on household focused intervention. The ZAMSTAR disease model was written by Pete Dodd, senior research fellow in mathematical modelling at the School of Health and Related Research (ScHARR). The model is a complex individual-based household-structured model of TB transmission, HIV and TB disease progression, aging and household-movement designed to investigate the effect of various interventions on TB and HIV prevalence. TB is notoriously difficult to model, mainly due to the nature of the disease which – similarly to coronavirus – means healthy individuals can be infected without experiencing noticeable symptoms. 

My MSc project was on the calibration of the ZAMSTAR infectious disease model. Calibration is a computational method which can be used to improve the accuracy of predictive outputs.

How has your degree helped you in your career? 

My MSc in Statistics has given me an excellent grounding in applied statistics from sampling theory to several machine learning techniques. A broad grasp of statistical theory meant that I am able to interrogate datasets much more effectively and design methodological approaches.

I also prepared many ºù«Ӱҵ assignments using RMarkdown. Automation has become increasingly common in government where we are now using more efficient methods like Reproducible Analytical Pipelines (RAPs), which incorporate elements of software engineering best practice and programming languages like R and Python into analytical work.

What scientific skills did you develop during your course?

I came to ºù«Ӱҵ with no computer programming background, having done a pure mathematics degree. Learning statistics through the medium of R developed both my coding techniques and statistical knowledge at the same time.

What transferable skills did you develop during your course? 

The applied elements in the course include how to structure a statistical report, as well as mock scenarios where you will learn how to present your findings to non-analysts. There is also a group project assignment – again, in the real world you obviously have to construct your own surveys or experiments, learn to work collaboratively on joint projects, and deliver the conclusions from that work within specific timescales.

What do you miss most about ºù«Ӱҵ?

I miss walking around ºù«Ӱҵ – which is surprisingly green, has the benefit of being hilly, and is only a stone's throw away from the Peak District National Park. It also has lots of nice pubs with a good range of ales, and a really friendly vibe! ºù«Ӱҵ is very much a university city where students are part of the buzz, and the local people are extremely welcoming. 

What would you say to a prospective student considering studying MSc Statistics at ºù«Ӱҵ? 

The ºù«Ӱҵ MSc Statistics course is really useful in today’s job market because it is both applied and broad in nature – while I could eventually have done my current role without an MSc in Statistics, I certainly would not have been able to be as successful over the same period of time or had the same confidence in my work. People often comment that I’m very passionate about statistics, but I really wouldn’t enjoy my job as much if I didn’t have the same depth of understanding given to me by the MSc.