Fiona Lau

What made you choose the MSc Data Science course at City St George’s, University of London, especially with your background in economics and finance?

Before considering a master’s degree, I was already trying to learn programming and data-related skills through platforms like Codecademy. However, I found it challenging to create a clear structure for my independent learning. After completing a course, I often wasn’t sure what to learn next or how to apply the knowledge in a meaningful way. Even after taking several courses, I struggled to translate what I had learned into real projects.

That led me to explore master’s programmes, as I was looking for something more well-structured and highly practical. When comparing different MSc Data Science courses, I paid close attention to the curriculum and how the courses were structured. I wanted a programme that provided strong theoretical foundations while also placing a strong emphasis on hands-on, practical work. Rather than focusing solely on exams, I was keen to develop my skills through coursework and projects where I could apply what I was learning in real scenarios.

My background in economics and finance had given me strong research and analytical skills, and I saw data science as a natural way to build on that foundation. The MSc Data Science programme at City St George’s, stood out because it aligned well with these goals and offered a balanced mix of theory and practical application.

Which practical skills or tools from the course have been most useful in your career?

Python and machine learning have been fundamental to my career, as they underpin most of the work I do today. These skills form the technical foundation for building, experimenting with, and deploying data-driven solutions across different problem domains.

However, one of the most interesting and unexpectedly valuable parts of the course was Information Retrieval. This module focused on how to retrieve information effectively and, crucially, how to evaluate the quality of retrieval systems using appropriate metrics.

This knowledge became particularly useful when working on Retrieval-Augmented Generation (RAG) systems with Large Language Models (LLMs). The principles from information retrieval helped me make informed design decisions and assess whether the system was actually performing well.

The combination of core technical skills and a deeper conceptual understanding from the course has been particularly valuable in my career.

How did your studies prepare you for your current role at Vodafone, especially in interviews and building your portfolio?

The course prepared me very well for my current role at Vodafone, particularly in terms of interviews and building a strong portfolio. Throughout the programme, I had many opportunities to work on different types of coursework, each requiring a different set of technical skills and problem-solving approaches.

Each coursework focused on solving a real problem rather than just theoretical exercises, which helped me understand how to apply data science techniques in practice.

These projects collectively became my portfolio. During interviews, I was able to talk through concrete examples of what I had built, the challenges I faced, and how I approached them from an end-to-end perspective.

While studying part time alongside full-time work, which services at City St George’s, did you find helpful in supporting your learning?

Studying part-time alongside full-time work was very manageable thanks to the way the course was structured. It was particularly helpful that I only needed to attend university one day per week.

I also found the campus facilities very supportive of my learning. I spent a lot of time in the library and the canteen in between classes, using those spaces to prepare for lectures, review coursework, and study.