Speaker Spotlight: Q&A with Dr Rebecca Pope, Head of Data Science and Engineering @ KPMG

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Dr Rebecca Pope speaks to us about her role in the technology sector and shares her thoughts on London’s Women of Silicon Roundabout, taking place 25-26th June 2019.

Dr Rebecca Pope is a clinical neuroscientist, TEDx speaker and part of KPMG in the UK’s leadership as its Head of Data Science and Engineering. She leads KPMG in the UK’s Centre of Excellence to build scalable, high-performing data science and AI products to help transform and drive business value across the KPMG global network’s client base and across market sectors.

Rebecca is an internationally recognised thought leader and an implementation expert in how technology and data science can accelerate improvements in health and care. She has published a number of academic research papers, written several scientific commentaries in the Guardian, and is the recipient of national awards for her academic research. She has co-authored numerous KPMG Thought Leadership papers.

Rebecca is an active and passionate member of various initiatives to foster diversity and inclusion in STEM, from school to the C-suite. She will be sharing her wisdom in a session entitled 'Top Tips For Launching into a Career in Data Science' at 13:40 on 26th June.

Which tool should you learn – R or Python? Which techniques should you focus on? How much statistics should you learn? Do you need to learn coding? These are some of the many questions Rebecca will be answering during her presentation.


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We caught up with Rebecca ahead of the conference, here's what she had to say. 

Please tell us a little bit about yourself and how you got to where you are today.

A little about me, well I love kayaking, classical movie music, being at our allotment, and generally any sport that doesn’t require high demands of my left knee! By background, I have a PhD in Clinical Neuroscience and, as a consequence, I have had the privilege to share in the lives of individuals undergoing neurosurgery for epilepsy and brain cancer.

I explored a career in Data Science due to my neuroimaging background, which is really a ‘big data’ time-series problem. This led me to investigate more about the field of Data Science, specifically Machine Learning, and the possible applications to healthcare and that was it…I was hooked. I knew that I wanted this to be my career.

So, I invested a lot of my spare time into swotting up on the techniques in the field, attending hackathons, upskilling, and started applying for Data Science roles that clearly aligned to my personal values: the ethical application of data science and artificial intelligence products to improve health and social care for all.

Over a decade later, here I am: Lead Data Scientist specialising in the use of AI within Healthcare, a TEDx speaker on the topic, and Head of Data Science and Engineering at KPMG.

What is your reaction to the fact that women hold just 24% of computer science jobs?

Well, sadly, I am not surprised. Given the expansive reach of technology in our lives and society, I think it’s genuinely worrying that women – let’s not forget this is nearly half of the UK workforce – are underrepresented in the sector. Technologies must be developed with diversity and inclusion at their core and benefit from the power of diverse thought.

As a firm believer in being the change you want to see in the world, I am an active and passionate member of various initiatives to foster diversity and inclusion in the field, from school to the C-suite (e.g., KPMG’s ‘IT's Her Future’); so I hope in a small way I am helping females of all ages pursue a career in technology.

What’s a typical day like for you as Head of Data Science and Engineering at KPMG?

My day always begins with checking in with my team (in the office or via Skype). I am fortunate to have a brilliant managerial team to support me in ensuring that my team has an environment in which they can be at their best and, ultimately, build scalable, high-performing data science and AI products to transform and drive business value for KPMG’s global client base.

Roughly half of my time is buried in code, normally Python. This may be training, testing, optimising Machine Learning (ML) algorithms or reviewing other team members’ ML builds. I am accountable and responsible for my team’s technical delivery, so remaining as a ‘hands on keyboard’ data scientist, despite leading the team, is really important to me in my career.

The rest of my time is divided between business development, client meetings, personal learning, certifications and trying to keep on top of a burgeoning inbox!

Machine Learning and Big Data

What is your Women of Silicon Roundabout talk about?

My talk will discuss my Data Science journey and explore personal lessons learned for those who are considering a career in Data Science; common misconceptions of what being a data scientist involves and the skillset you need to nourish; tips on how to become a (software) Swiss army knife and the importance of embracing failure – after all, we back-propagate errors in our Machine Learning algorithms to improve performance, let’s embrace the same approach to Data Science learning!

What are you most looking forward to at Women of Silicon Roundabout?

Learning from other technologists; networking and meeting fellow STEMinists! I am always on the lookout for passionate technologists as KPMG have a vibrant and ever-growing technology practice.

What advice would you give to women who want to pursue a career in STEM?

Don’t focus on what you don’t know, but your ability to learn (not what you have learned). Embrace free learning materials (MOOCs) before considering a financial investment in a ‘formal’ qualification; most companies care about what you can deliver and build, not what university you attended or the letters after your name.

Read Sheryl Sandberg’s ‘Lean In’ book – as a female starting out in technology many years ago, it was a fantastic read and I still use a lot of the content in my career today. I would also advise you to find a mentor that will support and challenge you in your career.

Finally, just go for it – what’s the worst that can happen?

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