An Interview with a Data Scientist

Tell us about your current role?

I work as a Data Scientist at Nomura where I support the Chief Data Office. My work focuses on advanced analytics for various use cases, building and deploying machine learning models to support governance processes, and detecting anomalies within various data pipelines. A key part of my role involves collaborating with stakeholders from various functions, whether it is risk or global markets to better understand the data and domain of the problem at hand.
 

Where did you start your career and how did you progress?

I started my career with a consultancy company. They trained me in data governance with data analytics on the side. However, when placed on site at Nomura, I quickly found that I preferred the analytics side of things, and actively sought to upskill in coding and mathematics in a way that would allow me to apply this to my role. I was fortunate enough to have my managing director recognize these efforts and push me towards becoming a data scientist. 
 

What are some of the highlights and challenges in your field?

I'd say the main highlight is that it is intellectually stimulating. As juvenile as it may sound, it is just fun to build solutions and products to solve data related problems. There is so much to learn, which is a double-edged sword. Whenever you feel like you know something, there is a greater mountain to climb. The biggest challenge is the business side of things. It is not as glamorous as working away on some obscure dataset, finding amazing insights, developing a model and saving the day. Often there is a lot of back and forth with the business, realignment of priorities and pivots. Often it is less about the technical skill and more so about knowing what problem to solve and why. In addition, real life data is often extremely poor. A lot of time is spent cleaning and trying to gain intuition on whether something makes sense in the dataset and why. Without this step, you run the risk of having extremely poor models.
 

Could you describe what a typical working day looks like for you?

I'm currently studying a part-time MSc in Artificial Intelligence, so my days start a little earlier at 6-7 as I like to study before the day starts. Recently I have escaped the need for daily stand-ups and updates happen as and when needed. That means I get a lot of time to consider solutions and analyze the complex datasets that are given to me. This time is quite crucial given then range of stakeholders we work with and the variety of datasets. 
 

What are the most important skills for professionals in your field to have? 

The obvious ones are statistics, coding and knowledge of the lifecycle of a trade. On the soft skill side of things, the ability to articulate your ideas is key. It doesn't matter how dazzling your solutions are, if you cannot explain them, or justify why certain approaches were taken, then you can run into problems. Explaining technical solutions in plain language is crucial and the only way to do that is to really know your stuff. There are so many ways to develop these skills. I have had a lot of success with using GPT to outline certain concepts I want to learn and then providing me resources to study from. I can then iterate over that. You must be careful though with the possible mistakes GPT will make. Always double-check facts and go deeper. It can seem daunting at first, but if you do something every day or average out a good amount of studying over a week, you will begin to build a solid foundation in the required areas. You can use multiple resources to learn about the same thing (in fact I'd advise it) and then stitch it all together in your mind. Projects also help a lot - you learn most when you are building something. 
 

You earned the Certificate in Quantitative Finance (CQF). Why did you decide to enroll and where has the CQF added value to your career?

I decided to enroll on the program because I have always been interested in the trading aspect of the financial markets, and I saw it as a great way to expose myself to that, whilst also developing my mathematics and coding skills. The way it has shaped my mathematical thinking, has helped me tremendously and inspired me to take my studies further - helping me get into a MSc program for Artificial Intelligence. It has also allowed me to have more fruitful discussions with stakeholders and have discussions related to financial products.
 

Do you think the industry has changed since you started, and how do you see it changing in the next few years?

The industry has changed massively particularly with the proliferation of generative AI. I cannot really say where I see the industry changing in the next few years, but it seems unlikely that we will have agents completely automating away our jobs, due to the regulatory and explainability requirements in banking. Then again, I could be completely wrong. All I know is that it is important to continuously upskill to make sure that when big changes do happen, you are ready.
 

What would your advice be to someone starting a career in your field today?

Focus on getting your foundations right - strong mathematics, clean coding, and financial intuition. Build small meaningful projects and learn by doing. Read widely and, overall, enjoy it. It is a stimulating field, and you do not need to know it all from day one. Fall in love with not knowing and the process of acquiring information. Consistency matters a lot more than speed!