A year ago I decided to change jobs, leaving my role as a statistician at a contract research organisation to pursue a career working as an academic. I remember telling friends and family about my new job, saying how “it’s still in clinical trials so the jobs are very similar”, which I quickly discovered just isn’t true. Even though there are many similarities, such as still working on clinical trials, the demands and the focus are very different. I wanted to write about this to share my story to help anyone starting their career as a statistician but unsure which is the right path for them, or for those like me that might be looking at swapping between the two. I hope that this blog provides a taste of the two perspectives through my own experience.
In 2017 I interviewed at IQVIA, one of the largest CROs, where I was accepted as a Biostatistician in the Clinical Trials department in Reading. This was my first role after graduating with an MSc in Medical Statistics and I was excited to apply all the things I had learnt during my degree. I spent my first few weeks learning more about the trials processes, learning SAS programming and reading plenty of SOPs. The company has a great training scheme to really ensure graduates are well supported and can get up to speed quickly with the workings of clinical trials. The work at CROs, in general, is fast-paced, varied and there is plenty of exposure to all the elements in the analysis of trial data (from writing statistical analysis plans to writing programmes to producing tables and figures for analysis reports). As someone just starting out in clinical trials this job gave plenty of support to help me find my feet.
During my time working in industry the main priority was meeting client timelines and generating trial results across the various projects I worked on. The project teams were usually quite large and could often change, therefore I needed to be adaptable and be able to pick up the project tasks quickly to meet deadlines. Each week most of my time was spent on project work and after initial training only a small percentage of my time was allocated to training and development. A useful tip I learnt when working in these larger groups was to speak up if there were particular tasks that were of interest to me, as this meant I could gain the experiences I wanted. The teams were almost always very receptive of this and would always try to factor preference into projects.
After a year working in the industry I realised I wanted a change to academia. Although I was enjoying the work, I didn’t feel like I had made a personal impact. The large team size meant I often felt very detached from projects, and not able to truly understand the research questions. At times I would be coming onto a project to simply implement the code elements of a statistical analysis plan or update outputs. The elements I enjoyed were the challenges without obvious solutions where I would spend time researching and understanding the problem in detail to find solutions. This was always very rewarding and would help me feel like I had a greater understanding. I felt the move to academia would offer more opportunity to do the things I enjoyed, including research into digital health, an area I was passionate about.
So, in April of last year, I made the move to Imperial College London to work at the trials unit on digital health trials. In this academic role the first big difference I noticed is that the size of the statistical team working on a trial is much smaller, it might just be you and a senior statistician. This changed my focus, as now more attention to detail is required, whereas in industry any mistakes might be picked up by other team members, here they might not. However, a smaller team has meant more direct contact with the trial team such as the chief investigator. Having more direct contact meant more control over my own timelines and helped me build a stronger understanding of clinical trials. For me I have really enjoyed the change, I have become more confident in many aspects of my research, which in turn has helped me become a more effective statistician.
Additionally, as an academic, my focus for career progression is around research outputs. This has pros and cons, as on one hand it means I have more time to focus on research questions and pour over the results in detail. However, it can sometimes lead to more pressure to generate results in a timely manner to meet deadlines for conferences or other scientific events, as well as pressure to write publications. Working as an academic, I’ve realised it is important to have an idea of what area you want to focus on. In trials, statisticians must work collaboratively with clinical colleagues, and it is all too easy to help other researchers in their interest and forget about your own. Developing your own specialism early can help keep you motivated and the work enjoyable, as well as helping your career.
In summary, it’s important to consider differences in the two roles and what is the best fit for you. An industry role with exposure to a broad range of experience and support by a large team, or an academic role where experience is more in-depth, and you can have more of a personal impact. However, as you can see with my experience there is always an opportunity for experience in both.