Healthcare data is not just a collection of numbers – it is a treasure trove of insights waiting to be unlocked.
Meet Millie, a data scientist from the Data Analytics and AI (DNA) Centre of Excellence, who switched careers from marketing and now helps bridge the gap between cutting-edge AI and real-world healthcare needs. By collaborating with diverse stakeholders, Millie transforms raw data into actionable solutions, paving the way for a more efficient and personalised patient experience. We delve into Millie's career switch journey, sharing the potential of AI in healthcare and offer practical tips for those seeking success in this dynamic field.
Embarking on a new path: Millie’s career switch
Millie transitioned from a marketing role to becoming a data scientist, as she was driven by a desire for a more technical and analytical career path. Her love for solving puzzles naturally translated into a passion for tackling challenges in data science. On top of that, Millie was particularly drawn to the HealthTech industry as she came to the realisation that people dedicate a significant amount of time to their jobs. She wanted to make it count and have a lasting impact. After careful consideration of what constitutes a “meaningful and fulfilling” job, Millie decided that she wanted to join the HealthTech industry, whereby it combines the meaningful aspects of healthcare with the innovation and growth opportunities of the tech industry.
There’s a lot of exploration involved in data science. There can be multiple potential solutions for the same data science problem, like how there are multiple hiking paths to the same peak. It is only through exploration that we can decide what is the optimal one for the particular use case.
Encountering roadblocks and overcoming them
Entering the data science field presented Millie with some significant challenges that she had to overcome. Inexperienced in any coding languages and lacking relevant prior working experience, she knew these shortcomings would drastically affect her chances of landing a data science job. Undeterred, Millie embarked on a bold career move.
Taking a gap year from work, she enrolled in a Masters of IT in Business programme to gain a deeper understanding of the field. But her learning did not stop there. Millie actively self-learned, immersing herself in videos on model architecture and statistical concepts. She subscribed to relevant data science newsletters and sought guidance from those who made similar career transitions to better prepare herself.
To Millie, the Masters of IT programme was not an easy feat. She had to play catch up on her technical coding skills while simultaneously grasping the theoretical concepts. While the workload kept her schedule busy, she fostered a sense of camaraderie with fellow course mates who were in the phase of changing careers as well. Discovering this supportive community of peers made her journey far less lonely.
