We found it hugely inspiring to hear such personal views from someone making a real success of being a Data Scientist and adding tangible value to businesses. We would love to hear more stories like this so please do get in touch if you would like to talk to us.
Life as a Data Scientist | Sarah Wynne
JF: So Sarah, kicking off what do you see as the biggest opportunities in analytics?
SW: There are so many to choose from as the tools we use for analytics become faster, more powerful and accessible every day. For me, I can see huge benefits in introducing more businesses to the power of Big Data. In the past, it was difficult to take business data and carry out an end to end analysis investigating real business issues, like the loss in profits for example.
Nowadays, we can produce a granular statistical analysis of millions of rows of data and the results can help quantify and target issues, often challenging an existing belief about the source of the problem. We know some business sectors are doing this well already, but there is still so much opportunity for others to move into this space.
JF: Given your experience of delivering in this space, what have you seen as the biggest blockers to organisations exploiting the value from data?
SW: Poor access to data and data integrity issues are the most consistent blockers I have encountered across all companies. Many legacy systems were not designed for large scale data analysis so getting hold of the information can be a nightmare. Then once extracted, the amount of cleansing that needs to be done can be massively time-consuming.
As we move towards Cloud-based data storage solutions I hope to see that the former problem is reduced, but I think it would be great if we could all challenge our organisations to maintain data integrity to prevent time wasted cleaning dirty data. Who knows how many hours of valuable analyst time that might save.
JF: You’ve had a great career so far, are there any female role models in business or in analytics that you look up too?
SW: I recently met Kim Nilsson who is founder and CEO of Privigo, a company which provides consultancy services but also helps analytical PhD post grads transition into careers in data science. I found her story inspirational, particularly as she is a female entrepreneur and data scientist, two areas of business where females are in the minority.
Also, I am very lucky as my mum has always been the strongest female role model in my business life due to her work ethics. As far back as I can remember my dad worked long hours often away from home and my mum looked after me and my two sisters. When we were all still in school my mum decided to go back to university and got a placement at Exeter to do a PhD in Paleoentomology. How she managed to juggle a PhD and three troublesome teenagers I have no idea but she taught me that all of my ambitions can be achieved, it just takes hard work and determination.
JF: Are there any other people or things that inspire you in this space?
SW: I love maths and science literature and I’m always scanning the news for new and exciting articles in this area. Alex Bellos really inspires me, he has written some fascinating books on the link between numbers and the world around us and I also find books such as “How not to be wrong, the hidden maths of everyday life” (Jordan Ellenberg) and “How to predict the unpredictable” (William Poundstone) really interesting as they all describe mathematical theorems in ways that everyone can understand and relate to. That’s what I aim for in my work.
JF: Data science continues to be a hot area to get into. Are there any skills that women, in particular, bring to analytics to be applied in business?
SW: The most important skill I think an analyst can bring is the ability to simply and clearly explain complex analysis to non-analysts. The decision-makers of the corporate world may not be analytical and no matter how much you believe that your analysis will help them, they will not implement it unless they understand how your work will bring them the benefits. I have worked with women in the past who have really excelled at this skill, perhaps more than men, but it’s a hard one to quantify.
JF: What skills would you recommend to those wanting to get into Data Science? Male or female.
SW: I have a strong interest in maths and statistics, I studied economics and mathematical sciences at uni and have developed some of my programming skills in languages such as R since then. However, for a long time, my role as an analyst put me somewhere between IT and the business, developing analytical solutions to guide the business to the areas that needed focus. It required a large amount of stakeholder management and problem-solving outside of my mathematical models and this finally led me down the consultancy path. For me, a data scientist isn’t just someone who churns through data all day applying models. This is, of course, a part of it, but having a balance of those skills mixed with business and innovation can lead to more powerful analytics.
JF: To finish off, what are your career goals and how close are you to achieving some or all of them?
SW: My plan has always been to work for myself being successful at something I love so I guess I could say that by setting up my analytical consultancy, I am almost at my goal. Perhaps success is a moving target, but I get great satisfaction out of the knowledge that I have helped organisations optimise their business through data and analytics. We spend so much of our time at work that I think job satisfaction should really be a top priority in people’s lives.
JF: Thanks Sarah, hugely insightful and I appreciate your time today.