Réka Nagy works as a Scientist working to develop new ways to analyse large genetic datasets. Here she shares her career journey and how communication is key. Name Réka Nagy Degree Course BSc (Hons) Biological Sciences (Molecular Genetics) PhD in Statistical Genetics Year of Graduation 2013, 2017 What path has your career taken since graduation? After defending my thesis, I stayed on at the University (within the Institute of Genetics and Molecular Medicine) for half a year, as Public Engagement Officer and Postdoctoral Researcher. This role was created specifically for me due to the substantial amount of public engagement that I had done throughout my PhD. Throughout my PhD, I became increasingly certain that I would like a career outside of academia, so I applied for both scientific roles and science communication/ public engagement roles. I got my first 'real job' in February 2018, with a company called Genomics plc, and I still work for them today. I work as a scientist for Genomics plc, which is a University of Oxford spin-out that tries to understand the human genetic 'wiring diagram' by developing new ways to analyse large genetic datasets. Some of our areas of expertise are a better understanding of disease genetics; the ability to identify novel genes that could be viable drug targets; or the ability to develop individual genetic risk scores to, for example, supplement clinical screening. In my day to day work, I get to do a lot of coding to wrangle and analyse data. I also use my biological expertise to glean insights from the results, and a large part of my work also involves coming up with ways in which to best visualise and communicate these results both internally, and to our collaborators. What experiences do you feel helped you get to your current position? I think everything I did while at University has contributed in a small or large way - the work I do is directly relevant to what I was working on during my PhD so I can apply the same statistical, and programming skills. It also heavily relies on the biological knowledge I have amassed during my undergraduate training - statistical analysis can get you so far, but to make meaningful insights from the numbers, you also needs to understand how the genetic variants affect biological systems to lead to certain diseases. My participation in team competitions/activities throughout University (e.g. iGEM; BioYES) really helped me learn how to work well as part of a larger group of individuals, and has helped me identify my strengths and weaknesses in this area such that I can decide what tasks I would most efficiently be able to contribute to. Having written for the University student newspaper, and having been encouraged to participate in (and in some cases win!) science writing competitions means that I am able to communicate well in writing. Additionally, organising or interacting with visitors at science communication events (for example Edinburgh Science Festival, Doors Open Day, presentations at local schools, or the online 'I'm a Scientist, Get Me Out of Here' competition) in addition to presenting at scientific conferences and meetings, have all made me into a proficient communicator who can engage a wide variety of audiences. This really helps in my current work, where I have to clearly communicate my ideas/results to colleagues whose expertise may be in biology, statistical genetics, computer science, pharmacology, or a field entirely unrelated to any of these. What advice would you give to students who are interested in your area of work? Whether it's a role within academia, or a role within a company, that you're after, you can feel assured that your skills are going to be in high demand. Be sure to highlight your technical proficiencies but also anything else that you have 'coincidentally' become proficient at due to extracurricular activities you have done - these will set you apart from other candidates who might also have a similar level of technical training, but may lack some of the 'nice to have' skills. This article was published on 2024-10-28