Learn more about the life of a Technology Analyst
I’d only been coding for a year before I joined Barclays. I studied Mathematics and Data Analytics at university so my tech knowledge was theoretical rather than hands-on. In fact, up to the age of 22, my only coding experience consisted of printing ‘Hello World’ onto my computer screen! However, you don’t need a degree in computer science to do most tech jobs. You just need be an open-minded, eager learner.
Barclays enables you to learn on the job, giving you hands-on experience in real-life projects right from the beginning. My team is open and collaborative so if you’re struggling with a particular problem someone will give you a helping hand. This is by far the best part of working at Barclays – the open, diverse and friendly environment where everyone encourages everyone.
You don’t need a degree in Computer Science – you just need to be an open-minded learner.
My knowledge and skills have grown exceptionally since joining: my generic tech skills but especially my coding skills. When I look back now at code that I wrote when I first joined, I realise how much I’ve learned.
As a data scientist, I do everything from coding, data analysis and model building, right through to establishing business requirements, stakeholder management and presenting insights and results.
My direct team are mainly based in the Radbroke office so we usually engage over video calls. Whilst working on projects, our team usually collaborate using Git and Jupyter Notebooks. In terms of tech and coding languages, I mainly use Python and PySpark but R and SQL sometimes come into play.
Data science is pretty much applicable in any area of the bank. Our area has worked on a wide variety of different projects, from combating financial crime to improving customers’ banking journeys. One particularly interesting project was building a machine learning model to predict accounts which may be undertaking mule-related behaviour (i.e. the transfer of illegally acquired money). This project helps to flag up potential mule accounts before the bank would normally have manually identified them – saving both the bank and customer’s time, money and reputation, whilst adding that extra level of security.
Data Science and Machine Learning are quickly becoming a key area of focus for many companies across all industries. I’m excited to see how this area will progress in the coming years at Barclays, particularly with the move to Cloud, and how our machine learning capabilities will grow and expand and be at the forefront of innovation. I am also passionate about encouraging more young people into technology-related careers, particularly those from under-represented backgrounds. As a Data Scientist at Barclays, I feel I have the platform to make a difference.