I confess, when I joined IBM as a data science consultant, I had only a limited understanding of the responsibilities and challenges involved. In retrospect, it has turned out to be one of the most rewarding decisions I’ve ever made.
Before joining IBM, I studied Biomedical Engineering at King’s College London and spent a year working with researchers at Siemens Healthineers. During my time at Siemens, I used data science to implement an image correction algorithm for the new generation of MRI scanners. This experience equipped me with a strong foundation in medical devices, biological systems, and the world of AI. However, as I delved deeper into the field, I realised that data played a pivotal role in understanding and transforming every industry, not just healthcare. Recognising the importance of data, I decided to steer my career towards data science and analytics, a field that is rapidly evolving in every industry.
After completing my degree, I was fortunate enough to join IBM as a data science consultant. IBM’s reputation as a leader in technology and innovation was a major draw for me. Additionally, IBM’s commitment to leveraging data and AI to drive business and societal transformation aligned perfectly with my career aspirations.
I am now just over a year into my journey at IBM, currently working on a high-profile project for NHS England (NHSE). NHSE is one of the largest public health systems in the world and I am the data analytics lead and subject matter expert for the NHS App, one of NHSE’s many exciting projects. My role consists of two areas; extracting and deriving useful business insights from the data and interacting with stakeholders across NHSE to help paint a picture of what the insights show and how they should inform the next business decision. The nature of the analytics I work with can impact NHS and government strategy with many of my reports and insights being provided to the Secretary of State for Health and Social Care as well as Select Committees.
I work with a range of technologies including Postgres, Splunk, Adobe Analytics and Power BI, which are predominantly data technologies, but I also work with Python and Microsoft Azure. I would highly recommend upskilling in Python as it is a skill that can come in handy for a wide range of use cases. When I joined IBM, I didn’t have most of the skills I just listed but rather learnt them on the job. But that is the nature of consulting – it can be challenging at times, but you get the opportunity to pick up and learn new skills quickly and then apply them to solve real world problems.
You might wonder how a young consultant has been given the responsibilities I just described? The answer is simple – at IBM, if you are willing to work hard and show that you can handle these responsibilities then there isn’t much holding you back. There isn’t any of that hierarchy stigma and your career and the opportunities it provides is totally dependent on you and the value you bring to the team.
Transitioning from biomedical engineering to data science and analytics at IBM has been an incredible journey filled with learning, growth, and meaningful work. I’m excited about the opportunities that lie ahead as data science, analytics and AI continue to shape the future of industries worldwide.
If you’re considering a career change or wondering how your skills can be applied in the world of data and AI, I hope my journey inspires you. Clients like NHSE offer the opportunity to work on incredibly meaningful projects whilst developing the critical skills needed to ensure a successful consulting career. With determination, a passion for learning, and a commitment to making a positive impact, you can embark on a rewarding career, just like I did with IBM.