Dicle Bulut

Can you tell us about your academic background and what you studied at UCL?
I studied Philosophy, Politics and Economics with Social Data Science at UCL. My last year of studies consisted of data science, machine learning and asset pricing classes. I wrote my dissertation on the effect of air pollution on Green Party votes in the UK using fixed effects. I wanted to study PPE because it enabled me to keep the interdisciplinary perspective in my academic life while I pursued my more specific interests in depth. 

Could you describe your experience with the internship scheme offered by the UCL Social Data Institute? 
I interned at a Non for profit organisation in the summer of 2022. It was an overall fascinating experience, enabling me to learn about hands on applications of economics as well as networking with leading thinkers of this area. I wrote a 'Commodity Tracker' newsletter for other economists in the organisation to read. I compiled the information available to me and presented in a concise way to reflect the state of the commodity market to inform my colleagues. I learned to use Macrobond, a strong data tool for the industry and I debuted my Python adventure by writing a machine learning model to facilitate insight classification in the organisation.

How did the internship experience influence your decision on what career path to pursue?
I realised I am more interested in the technical analysis side of things to provide insight to my stakeholders, therefore I focused on the data science part of my experience to shape my career. My skills in collaboration, communicating data insight and being able to write a model for a specific purpose from scratch had a direct positive impact on my interview and my securing of my current role. 

Were there any specific experiences from your internship that you highlighted during your search for your current role?
The data storytelling insights I learned from the more senior people in the organisation helped me understand what is valued in this area of work. My work with 'Economic Deep Dive' part of stakeholder briefing helped me put numbers in a narrative to convey a perspective to less technical people. This turned out to be a very valued skill. 

Can you tell us a bit about your current role and what your job entails?
I am a Graduate Data Scientist at British Airways. I maintain dashboards and deliver insight to business partners for 'People' business area. My daily job consists of data reporting, developing tools to facilitate daily processes and maintaining data visualisation focused portfolio items. The most rewarding aspect of my career so far has been being able to showcase my technical abilities to solve complicated problems in the business and getting recognition for that.

What advice would you give to current students who are considering applying for internships?
They should be strategic in terms of which scheme to choose. They should choose a scheme in an industry they want to cultivate a relationship with. They should also focus on what kind of skills they are hoping to learn while choosing. We shouldn't lose the sight of the fact that majority of daily work of a data scientist consists of fixing and maintaining things rather than constantly innovating. It'd be useful to manage the expectations beforehand.