Dr Rebecca Pope has a PhD in Clinical Neuroscience from our very own UCL and now works as a Data Scientist at IBM. Rebecca sat on one of our Researcher Careers in Technology panel events and kindly agreed to give us even more of her time by answering a few questions for our blog.
How did you move from academia to your current role?
As a data scientist at IBM, I do not feel that I have fully ‘left’ academia strangely. I still publish in academic and non-academic settings; use my doctoral skills (clinical neuroscience) in Watson Health; and a must of this job is knowing that the more you read the less you know! So very similar to an academic post. However, there is a divergence in my responsibilities compared to my doctoral and post-doctoral experience, in that I am regularly meeting with clients and developing business opportunities. Thus, I have needed to develop and enhance my soft skills. My audience are usually non-technical and it is my job to relay the complex in an ‘actionable’ way for my client, which mean they need to fully understand IBM’s findings – that is the ‘art’ within data science.
I found out about the sector due to my neuroimaging experience, which is really a big data time-series problem. This led to investigating ‘big data’ and reading popular science books on the topic. I then upskilled myself by doing a number of online free courses and decided that this was a space I wanted to apply to, and just did.
What does a normal working day look like for you?
My days are quite similar. In the morning, I will work through early morning emails, as IBM’s clients are worldwide. Then have a daily sprint with the team, discussing project statuses and any immediate blockers to a project’s success. However, the majority of my day, involves diving into some data (exploratory data analysis and applying machine learning algorithms, whilst keeping in mind the client’s business problem(s)). I may also have a number of client-facing meetings in driving healthcare, life sciences and pharmaceutical opportunities into IBM.
What are the best things about working in your role?
The team I work in has a great ‘work and play’ ethos; tackling real-world problems across different industries, although my passion is within health and life-sciences, and the endless pursuit of innovating and developing myself.
What are the biggest challenges you face in your work/what are the worst bits? (Please think about elements that might put others off, even if you don’t mind them.)
It can be challenging ensuring that all stakeholders within a project are 100% fulfilled by my work, as often a CEO has a different agenda to a CFO, for example. However, this is a talent and skillset that I need to keep developing and have the space and mentorship to do so at IBM.
Is a PhD essential for your role?
I don’t think so. In fact, the variety in our team of educational backgrounds is one reason I feel we are successful. This gives the team different lenses to view the same problem.
But the PhD skills I use on an everyday basis include: being comfortable with not understanding things, quantitative numeracy, and domain expertise for Watson Health engagements.
Where would someone go in their career from here?
I think this is entirely up to you, I am a firm believer that you make your own doors in life to walk through.
The great thing about being at a company like IBM is the breadth of opportunities and business units. This means that as your personal/professional interests change, you are likely to find an aligned role within the business.
What top tips would you give a researcher interested in this type of work?
My top tips would be to invest heavily in your communication and team work skills.
Most people with quantitative PhDs can crunch numbers, program etc., these are skills that do not set you apart, in my opinion, from other candidates. More important is how you come across and your manner. You spend most of your life with your colleagues and so you want to like the people you work with. Developing yourself in this way, and knowing this is half the journey; the rest I leave to you. Best of luck.