What’s the most challenging thing about working here?
As a publicly-traded company, there has to be a significant focus on ensuring that our financial performance meets investor expectations. Inevitably, this creates occasional conflict between focussing on long-term initiatives and maximising short-term profits.
As a Data Scientist, I would like to spend all my time focussing on the former: big, strategic projects that move some aspect of our customer experience or internal operations forward in a lasting way. However, I am often required to delay or deprioritise this work in favour of diagnosing the latest blip in trading performance. There is no pretending this is enjoyable work, though stakeholders are invariably understanding and patient when these incidents occur.
What makes Moneysupermarket Group unique?
I’d refer back to that noble mission again!
How has your career developed during your time at Moneysupermarket Group?
I came into Moneysupermarket Group from a consulting role at a global IT corporation where, despite the stated commitment to advanced analytics, I’d spent far more of my time developing Excel reports for program management.
On joining Moneysupermarket Group, initially as a Senior Data Scientist aligned to the CRM function at Moneysupermarket.com, I became quickly involved with truly advanced analytical work: using machine learning techniques to inform the content, timing and written style of our email marketing. This meant I had to rapidly become proficient in techniques I’d only been reading about up to now, but I had great support from managers and peers throughout this period.
After two years in that role, I was given the opportunity to lead a team for the first time, at TravelSupermarket. This presented new challenges, and lots of new things to learn around project and people management. Again though, in a hugely supportive and motivating environment, I was able to pick this up. In my time at TravelSupermarket, the team has improved all aspects of how the business leverages data, from ingesting new third party feeds to inform marketing operations, to embedding a data-driven recommendation system on our Holiday search results page, to completely redeveloping our BI reporting suite.
I now find myself leading a team spanning two businesses, having taken on responsibility for analytics at MoneySavingExpert in late 2019, and am looking forward to finding similarly novel use cases for advanced analytics within this famous brand.
What advice do you have for someone looking to join?
Use our websites, sign up to our emails, get very familiar with our customer experience and start thinking about what you could do to improve it. Our colleagues in Marketing, Commercial and Product all look for analysts to go beyond just giving the numbers and actually make a recommendation on what to do next. Also, think of a common analytical technique (regression, decision trees, PCA for example) and consider how you would explain it to a non-technical person: this is the interview question that most often trips candidates up!