
Programme: MSc Business Analytics (on-campus, full-time) 2017
Nationality: Singaporean
Study mode: on campus, full-time
Undergraduate education: BEng Electrical Engineering (1st Class), National University of Singapore
Current position: Researcher (Intelligent Data Analytics), NEC Laboratories Singapore
Your background
Why did you choose to study your programme and why specifically at Imperial College Business School?
I wanted to transition into a career which makes good use of my quantitative analytical skills and Data Science was an ideal choice. I compared a number postgraduate courses offered in the UK and I found the Imperial College Business School’s MSc Business Analytics course had the most comprehensive content, e.g. statistics, visualisation, machine learning, optimization.
In addition, the curriculum was regularly reviewed by an advisory board consisting of many industry leaders. I was confident the course would be highly relevant and hence opted to study at Imperial College Business School.
Your time at Imperial College Business School
What was the most important thing/learning point you took with you from the Business School?
The most important takeaway is that Data Science is such a fast growing and rapidly evolving field. There are so many other advanced machine learning techniques that are suited to solve different kinds of problems. To stay relevant in this field, we have to constantly learn new knowledges and techniques applicable in our chosen industries.
What advice would you give to a prospective student considering studying the same programme as you?
If you are considering a career in Data Science / Analytics, this programme at Imperial College Business School is the perfect place to start. The comprehensive core modules (from statistics to visualisation) help to build a strong foundation while the elective modules and project teaches you how to solve real-world problems using data.
To make the most of your time while at Imperial, I suggest to volunteer for data science related projects, namely DataSpark or ICDSS (Imperial College Data Science Society) projects. I had a great time coding and learning alongside talented people, while helping clients to achieve results with the use of analytics.
How do you view your experience of studying at Imperial since you left?
It was definitely an enriching experience to have studied in a world-renowned university. I am fortunate to have met a lot of brilliant students in the class. We learned from one another and had a lot of fun time together.
The Careers and Professional Development team also organised a lot of events and invited speakers from the industry. This provided me a good overview on what qualities / skills which employers are looking out for. Lastly, being part of the Imperial alumni network allows me to connect with other graduates from Imperial as well. I look forward to connecting with more Imperial graduates in future and expand my personal network.
How did you find living in London?
London is an amazing city and I do miss my time at Imperial. There is no lack of activities to do to unwind in your leisure time. My favourite pastime was to relax in a cosy coffee shop or have a simple meal in new dining places.
Tell us about your current job
How was your career transformed following your programme?
Possessing a Master Degree in Business Analytics from Imperial College Business School has helped me to transition into Data Science field. Although I worked in software industry before studying at Imperial, I did not have any formal qualification or experience in Data Science. The programme syllabus and projects helped me to acquire the relevant skills to be a data scientist. During the interviews that I had after graduating, most hiring managers were impressed by the amount of breadth covered by the programme.
What did you take away from your learning experience that has been most applicable to your current role?
My typical workday includes analysing data and building predictive models. The core knowledge acquired from the programme, such as statistics, machine learning, optimization and visualisation are all very applicable.
One important takeaway I learned from the projects I did at Imperial: understand the data and have a good appreciation of the problem before performing analysis. By adequately formulating the problem at hand, it will be easier to decide which analysis step to take (e.g. whether to perform more data exploration and feature engineering, or select a model which favours interpretability over accuracy) in order to achieve positive outcome for the project.
What is your current role like?
I currently work in NEC Laboratories Singapore (NLS) as a Researcher, focusing on data analytics. As a R&D lab, we performed applied research for clients. My role includes analysing diverse sources of data and proposed new quantitative techniques to improve organisational performance. I also work with other engineering disciplines (e.g. front-end designers, backend engineers, database administrators, software architects) to ensure successful application of the analytics technologies in the final product.
What do you enjoy most about your current work and what are the main challenges that you face?
I enjoyed utilising my analytical skills and quantitative aptitude to solve complex real-world problems. The core expertise of NLS is developing new social solutions to solve social issues (in areas such as public transportation, public safety, healthcare). It is heartening to witness my work creating meaningful contributions to the society.
As NLS focuses on specialised areas (e.g. public transportation, healthcare), one of the challenges was to build a good understanding of the problems faced in these industries and the inadequacies of current measures. I had to read a couple of research paper in public transportation to understand the key problems in this area.
What is your proudest achievement in the job so far?
I have been with NLS for only less than 6 months so I can’t claim I have achieved a lot. One of my proud achievements was during a Proof-of-Concept project. I built a detection model to predict when heavy traffic congestion is likely to occur. The authority sees value in this early detection of traffic congestion, which could help them better manage the traffic conditions.
Alumni community
In what way is remaining connected to your alumni network important to you?
Imperial College has a strong alumni network throughout the globe. I feel that it is a good platform to stay connected with alumni who shared similar interests and expand my personal network. I was fortunate to have met a number of amazing people during my time at Imperial and I am keen to maintain this connection.