post by Edwina Borteley Abam (2019 cohort)
My internship at Capital One started mid-November 2021 and ended mid-May 2022. Capital One is a credit card company originally situated in the US with two branches located within the UK in Nottingham and London specifically. I interned at the Nottingham branch over a period of 6 months, on a part-time basis.
The company has several departments and units. I was placed within the Data Science team which forms part of the wider Data group within the organisation. There are three main sections within the Data Science team namely Acquisition, Customer Management and the Bureau team. The Acquisition team concentrates on building models to score new credit card applicants. The Customer Management team focuses on managing and monitoring the behaviour of all existing credit card customers and credit line extensions and the Bureau team manages all data and information exchanged between credit bureaus and Capital One. For my daily work, I was placed within the Customer Management team and collaborated on two related projects- (Onescore2 and Challenger Model).
The internship:
Onescore2 project involved creating machine learning models to manage the behaviour of existing credit card customers. I worked together with my manager to build models to predict customers likely to default on their cards over a defined period of time. We used R (a statistical programming software) as the main tool for the project. The specific activities assigned to me on the project involved creating the R program files for executing the models, monitoring the progress of the models’ execution, collecting and interpreting model results, and updating the GitHub repository with project outputs. The previous knowledge and skills acquired from the Data Modelling and Analysis course in year two of my PhD helped me understand the technical details involved in the analysis and to carry out my assigned duties effectively on the project.
The second part of this project is the Challenger Model project and it involved building different models in Python to compare their performance with Onescore2. The project was an exploratory study of different conventional models in predicting the likelihood of default. The Challenger Model project serves as a baseline to compare with results from my PhD work, which potentially could form part of my PhD thesis. As this phase of the project is linked to my PhD work, I benefitted from the guidance and input of my supervisor. While working on the Challenger Models, I held periodic meetings with my manager, supervisors and other members of the Data Science team where I presented on progress and discussed possible directions for the project. I also took part in weekly stand-up sessions where all associates within the Data Science team shared updates on ongoing projects.
My reflections:
Looking back on my internship, overall the experience has been insightful, an exciting journey and a time of personal development. I have grown and evolved in several areas in terms of interpersonal and professional skills.
Upon arrival in the first week of the internship, my manager was deliberate to arrange informal meetings and chat sessions with other members of the Data science team. These introductions and chats exposed me to a range of people in various roles and at different levels of leadership in the team. It helped to quickly integrate into the team to create new connections and meet new people. Despite being naturally reserved, I enjoyed the conversations much as everyone was friendly. I was encouraged to step out of my shell to interact with more people. During my interactions, I seized the opportunity to ask all the lingering questions I had on the topic of credit scoring which is also at the heart of my PhD research. Each person was friendly and particularly eager to answer all my questions and chat about the work they do.
Apart from the Data Science team, I had the chance to speak with other associates in other departments of the company and that experience was reassuring and enhanced my confidence at the workplace. I got first-hand experience in mixing with different people from different backgrounds in an office setting and learning to blend with them. The conversations in the first couple of weeks opened up my understanding more on the details of credit scoring and credit cards. I got more understanding of how the different teams work together to make credit cards available to people and how customers are managed and credit lines extended. I had the opportunity to join major meetings and to hear updates on projects being worked on within the different departments of the organisation. This also gave me a wider view of other aspects of the business. I was able to connect how the theory of credit scoring I had read in books and research articles played out practically in the real world through this experience.
During my internship, I worked both from home and the office. Every week during the first few months, I worked three days at home and two days in the office. I found commuting to work on time a discipline to develop as this was my very first time working outside of industry. Although challenging initially but got easier with time. The regular catch-ups and progress updates with managers and my supervisor were sometimes strenuous and nerve-wracking, however, it trained my communication and presentation skills.
The work culture in Capital One challenges associates to give their best on the job but at the same time encourages relaxation and places such high priority on wellbeing. Unlike other work environments, I was surprised to find several fitness and relaxation points like the gym, tennis and pool table strategically placed in the Capital One building to support associates. In addition, during my internship, the company observed a day of fun activities for its associates every quarter of the year just to have a break from work. This shaped my perceptions about the working environment.
Capital One is the industry partner for my PhD and I was privileged to have access to their data for my PhD work. Through my connections with the team members, I was able to easily recruit participants for my first PhD study which I believe would have been difficult otherwise without the internship. Overall, I enjoyed the internship and the experience has been beneficial not only for my PhD but for my personal development.
