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Data Science at LBG

Moving into Data Science

After finishing my undergraduate studies, I worked for a Fintech start-up as Product Manager. I interacted daily with a team of data specialists. I fell in love with the work that the Data Scientist and Visualisation Engineer were doing. I therefore decided to take a year off to re-train and do an MSc in Business Analytics.

During my studies, I had the opportunity to work on projects to interrogate data, find patterns and build predictions. I absolutely loved it and wanted to make sure I could apply the same skills in my career.

When it was time to apply for jobs, I noticed that Lloyds Banking Group was hiring Data Scientists. What I found interesting about the role is that I could apply my new skills in many areas of the bank and not just within traditional banking.

The interview was the point where I realised that this was right environment for me. The Q&A was actually fun and my interviewers answered all the questions I had about the ways of working.


AI: Hype vs Reality Event

Continuous learning: working as a Data Scientist at LBG

When I joined LBG, not only did I have the opportunity to apply my new skills, but also to learn new ones. My colleagues were extremely supportive and they dedicated their time to help me fill gaps in technical knowledge.

The digital community often organise incredible learning sessions, which include group meetings to discuss projects that our colleagues have worked on inside and outside LBG. We also have a dedicated book club to cover content that enriches our technical knowledge.

One of my favourite learning sessions this year was a three-day hackathon to learn and build anything we wanted. In our group, we created scary images using a technique called “DeepDream”.

Working with the Responsible AI team

Before joining LBG, I did some research on discriminatory outcomes in Machine Learning. What I found remarkable is the engagement of the LBG leadership in this area. I had the opportunity through LBG to present my personal research internally, but also at external events and conferences.

I now work with the Responsible AI team and have been able to use a lot of the work I researched on personally. It's been a unique experience to combine my passion for Data Science and interest in Algorithmic Fairness in my current role.

Improving diversity

I originally come from Bolivia, but had the opportunity to study in Germany. During this time, I found myself often at environments where I was the only woman and the only foreigner. I can't express how intimidating it can feel to be one who is different. Not fitting-in can hold you back. It is therefore extremely important to not only improve diversity at the workplace, but also to create an environment that is welcoming to everyone.

At Lloyds, we organise many events internally to promote the profile of minority groups. We also engage with external events and institutions to attract groups of society that are not equally represented. Having participated in some of these events, I've been able to inspire and support those wanting to join a career in Data Science. This is one of the most gratifying experiences I've had in my career.


Diversity by Default Event

Tips to become a Data Scientist

If you're currently a student and want to become a Data Scientist, I highly recommend taking courses in coding, statistics, and, if possible, Machine Learning. You can also gain a lot of experience by working on an empirical project during your final project or thesis.

If you're not longer studying at university, there are great Data Science courses online that are affordable as in Coursera or part-time courses from institutions such as General Assembly.

Data Scientists come from all backgrounds - at LBG, you'll find colleagues who studied Psychology all the way to Physics. Each path has been completely different for each one of us. If you feel lost, I highly recommend talking to a Data Scientist to help you understand what can be useful for you (we're very approachable!).


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