BSc Economics, University of Warwick
Quantitative Trading Analyst, DRW
What work experience/internships did you have before beginning with Imperial College Business School?
Before I started at Imperial, I completed two internships. The first as a Markets Summer Analyst at JP Morgan and the second as a Markets Summer Analyst at Barclay's Investment Bank.
Why did you decide to study an MSc Business Analytics at Imperial College Business School?
I was very eager to gain the skill-set of a data scientist. With many industries shifting towards more data-driven business models, I knew that the skills gained by completing the programme would hold me in good stead for the future. I enjoyed the applied nature of the programme and the exposure to a variety of different modules.
Did you receive a scholarship?
Yes! The funding was very helpful and allowed me focus on learning, rather than having the pressure to search for jobs and internships.
What aspects of the programme do you enjoy the most?
The hands-on and practical nature of most of the modules was by far my favourite part of the programme. Most of the modules require coursework to be done in either Python, R, or SQL rather than pen and paper, which I found very refreshing.
Which has been your favourite module so far and why?
Data Structures and Algorithms and Big Data in Finance were my favourites. Understanding data structures and algorithms was fundamental for pursuing the later modules and I thought Heikki Peura (the lecturer) did an excellent job. The lessons and tutorials were structured very well since they had the right balance between lecturing and hands-on exercises. Despite my limited background in programming, I came out at the end of the module with a firm grasp of the Python programming language.
Big Data in Finance was particularly enjoyable since it addressed a new and challenging area of finance. We were introduced to more interesting and complex techniques in data science and learned about the nuances of applying traditional methods to financial data. Our lecturer, Professor Tarun Ramadorai, was brilliant and managed to keep us interested - even on Friday afternoons.
What has been the most rewarding part of the programme?
The group projects are often very demanding, both in terms of the level of analysis and the high presentation standards required. Some of the best academic moments came after spending hours on a Jupyter Notebook, translating it into a user-friendly presentation, and explaining our findings together to the rest of the class. Whilst the preparation required late nights and early mornings, seeing the projects through to the end was very rewarding.
What has been the most challenging part of the programme?
The volume of coursework can sometimes be difficult to manage, so it’s best to start working early!
How would you describe your cohort at Imperial?
Extremely helpful, sociable, and intelligent. I was pleasantly surprised to find that the students with more technical backgrounds would volunteer their own time to tutor students who needed extra help before exams. The social events were a great way to get to know everyone better and make life-long friends!
Did you have a favourite professor/lecturer and why?
In my opinion, Heikki Peura had the best-structured lectures and tutorials. I learned the most from his classes. Professor Tarun Ramadorai conveyed difficult concepts very intuitively and worked through lectures at a swift pace, which meant that we learned a lot. He also managed to inject humour into most of the lectures, which is often an overlooked quality of a lecturer.
What has been the greatest opportunity you have had at Imperial?
I was offered the opportunity to take part in a six-month internship on a Machine Learning team in an investment bank, which had reached out to Imperial and the MSc Business Analytics cohort specifically.
What clubs, societies or other activities have you been involved in at Imperial?
I was a part of the Business School Investment Fund Machine Learning team. We spent a few months developing a Machine Learning algorithm to trade stocks in the financial markets. Along with that, I also attended a hackathon hosted by Imperial Algorithmic Trading Society at Blackrock’s London office, where we developed a stock-trading strategy using sentiment data. Finally, I represented the Imperial men’s cricket First and Second XI teams.
What are your future career goals and how have they been realised since being at Imperial?
I wanted a job which combined aspects of data science, technology, maths, and finance. This programme gave me the perfect skill-set to apply to those roles and be offered a position to work as a Quantitative Trading Analyst at a leading firm.
Have you received any job offers since commencing your programme?
Yes, I was offered a role as a Quantitative Trading Analyst at DRW, which incorporates using Python to monitor models, analyse data and create trade ideas.
Where do you live in London and why did you choose to live there?
I live in Maida Vale, with friends from my undergraduate studies so it was convenient for us all. It's probably not the best area for Imperial students, since walking to the Business School takes about an hour.
When you’re not studying, what do you enjoy doing?
I love to stay active. I play cricket, tennis, and football and go to the gym regularly when I’m not studying.
If you had to move to London for the programme, what have been the benefits and challenges of moving to London?
Travel expenses can rack up very quickly, so consider the trade-off between paying higher rent vs having to travel less. Look for student deals at restaurants to save costs on food and always carry a reusable mug for discounts on your coffee!
What advice would you give someone who is thinking about applying for the programme?
The more you put into the programme, the more you’ll get out of it. It is a great learning experience and the return on investment can be very large!