Data Scientist at Starling Bank
Data Science Bootcamp
Key Skills Learned
- Python Programming
- Data Analysis
Where are you working currently, and what do you do there?
I work at Starling Bank as a Data Scientist. My current focus is on developing machine learning models to automate and improve the lending process. However, I also get involved with the engineering side of implementing and delivering machine learning models in production. I work with a team of Data Scientists, Analysts, and Software Engineers located around the U.K.
Can you tell us a bit about your education and career background?
I’ve always had a numerical focus in my studies and prior work background, which is what led to my interest in data science. I studied maths, economics, and statistics at university. After graduating, I joined the banking industry working in the risk department at Barclays Bank. I held many roles across the retail bank and the investment bank during this time so got to see the whole spectrum of banking. I also had the opportunity to work at BrainStation for a while as an Associate Educator in the Data Science program.
What motivated you to start digital skills training with BrainStation?
I had been planning on making a transition into the data science field for some time. However, as many people find out, it's incredibly difficult to maintain the discipline needed to self-study while working full-time. The other issue I had was that data science is a very broad field, and it was hard to work out what was truly necessary knowledge without any guidance from someone in the field.
I was attracted to the Data Science bootcamp at BrainStation for a number of reasons. First, I appreciated the relatively short time period, only 12 weeks versus 12 months for a master's degree. The course also covered many of the key concepts I had identified as core skills for Data Scientists from my own research. I was also impressed by the professionalism of BrainStation itself and the team that I spoke to.
What was the highlight of your learning experience?
Outside of the excellent course content, my favorite part of the learning experience was building friendships with the other students on my course. We were able to help each other out when studying difficult concepts. Many of us have stayed in contact since graduating. Having a network of colleagues and friends from the get-go in your new industry is an invaluable resource.
Can you describe the impact your Educator had on that experience?
Data science is an incredibly broad field and the job role can be poorly defined at times. Having Educators with industry experience was extremely useful as they were able to guide us towards the key skills and competencies we needed to get our foot in the door. They also fostered a fun, engaging, and collaborative learning environment that made the 12 weeks an incredible experience.
How has your BrainStation experience impacted your career?
Outside of the core technical skills for data science, one of the key skills I learned during the program was the ability to present data-focused work to different audiences. Tailoring technical presentations to stakeholders with differing levels of familiarity with data science concepts is crucial to the role. On a given day, you may be talking about your project with other Data Scientists and Software Engineers in the morning and then presenting findings to others in the wider business teams in the afternoon.
“Having Educators with industry experience was extremely useful as they were able to guide us towards the key skills and competencies we needed to get our foot in the door.”
Can you tell us more about your final project?
My final project was focused on methods of reducing bias when classifying online comments as toxic. Machine learning models learn from the data they are given. Unfortunately, many real-world datasets contain various societal biases that are then propagated by machine learning models that learn from this data. In the world of online comments, a disproportionate number of toxic comments are targeted at minority groups. This leads to models that have a tendency to classify any comment mentioning a particular minority group as being toxic, even when they may be positive or neutral in nature. My project explored looking at ways of using more advanced machine learning techniques, such as deep learning and text embeddings, to deliver less biased NLP models.
How has your bootcamp experience helped you connect with the tech industry?
During my time in the BrainStation program, I was exposed to various industry touchpoints such as presentations from working Data Scientists and in certain cases, tours of companies. These were useful chances to speak directly to people working in the industry, rather than reading second-hand information online.
Speaking from your experiences as a TA and as an Associate Educator, what steps should students take to make the most of their learning experience?
You have to be judicious with your time. It’s an intensive program and many topics and concepts are covered. Most importantly, this means you have to accept that you may not fully understand a particular topic and instead be willing to move on and circle back to it at a later date.
You should also take advantage of the resources available to you. If you are having a hard time with a certain bit of content and can’t solve it yourself, don’t hesitate to ask. The education team is there to help you!
What advice would you give to professionals considering a BrainStation course or program?
Take the time beforehand to consider your career ambitions and how a particular course can help you get to where you want to be. While it’s exciting to dive straight into learning new skills, I have found the people who enjoy the most success from doing a BrainStation course are those who have a decent idea of what their future ambitions are and how they can leverage their past experience with the new skills they will learn to achieve these ambitions.
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