At Akeso, our teams work alongside healthcare organisations to solve complex challenges through data, analytics and strategic insight. Archie, Graduate Data Scientist, shares what a typical day in the role looks like and reflects on his journey into healthcare consulting.
Day in the Life of a Graduate Data Scientist
Over the course of my degree in Natural Sciences, specialising in Astrophysics, it became increasingly clear to me that my future didn’t lie in academia. I tend to think quite practically, with my prior work experience being at a vineyard where I would operate machinery and program robot arms to automate physically intensive tasks.
Upon graduating, I was looking for a job with meaningful application that would continue to be intellectually challenging and allow me to lean on the aspects of my degree that I enjoyed most: problem solving, predictive modelling and analytics. A career in Data Science felt like a natural fit, especially in a field like healthcare where there is lots of opportunity for impact and access to complex, challenging data!
After seven months at Akeso, my day-to-day work has evolved considerably, with increased responsibility, client communication and involvement across various workstreams of a project. This reflects the opportunity for growth that Akeso provides, where you are encouraged to get stuck in from day one and naturally develop both communicative and analytical skills.
Often, the day begins with stand-ups with the project team and analytics team, both guaranteeing time to discuss progress and sound out ideas. Afterwards, I’ll plan my discrete pieces of work for the day and progress them, ensuring I am well prepared for any client interactions or further internal meetings.
Most of my time is spent building models and analysing data to support key pieces of work, a recent example being an activity redistribution model to support the reconfiguration of emergency services. The working environment at Akeso challenges me to take a thoughtful approach to problems, with an understanding that there is no one way to structure analysis. I mainly use Python and Excel as complementary tools to build interactive models and create detailed visualisations, but there is a broad suite of analytical tools available at Akeso and a key skill as a Data Scientist is choosing the right tool for the right problem.
Alongside the technical work, a key part of the role is engaging with clients. This can be presenting findings, explaining modelling approaches or helping translate complex analysis into digestible insights. Developing confidence in communication with colleagues and clients has been one of the most rewarding aspects of the role so far, particularly as someone naturally more introverted.
Looking back, there is certainly no defined path into a role like this. Experiences that may initially seem unrelated, a degree that doesn’t perfectly align with a healthcare environment or a more introverted character are not drawbacks, rather traits that define how you approach work and communicate with the diverse range of characters and skillsets present at Akeso and across healthcare more broadly.