Ben Houghton – Data scientist
My initial interest in statistics started at university (I studied mathematics at Oxford). Throughout my time at university, I took more and more statistics and probability courses as my interest grew, until eventually in my final year I was taking only statistics-themed options.
I didn’t have a very clear idea of what kinds of statistics roles existed, so I decided to join a graduate scheme to try and understand the kinds of jobs that might be available. I started my career in technology risk, from which I moved to database architecture and data warehousing, dashboard development and finally into a data science role, where I got my first exposure to machine learning, among other techniques.
I initially took to data science as a career choice as it allowed me to use cutting edge techniques in both the statistics and the computer science space to solve very interesting problems, many of which haven’t been looked at before due to the constraints of previously used analytics methods.
I am now in my third data science role in Barclays, having worked in the real time decisioning team during my grad scheme, and then the Big Data Centre of Excellence after that. My current role is as senior data scientist in the advanced analytics and monetisation team, working on a variety of problems across the bank.
In my current day-to-day, I split my time between running statistical analysis (often using R), building machine learning solutions (usually using Python) and building engineering pipelines on big data platforms (using Scala and Spark). The rest of the time is spent working with the business to shape the problems, guiding my team through the many different techniques and spreading knowledge of these capabilities to other teams in the bank.
One of the most exciting things about being a data scientist is the variety of work. The role isn’t necessarily limited to one type of problem or a toolset/technique, rather it is about solving big problems which have previously been unsolvable.
Take a look at our guide to becoming a data scientist.