Bachelor of Business Administration, Tianjin University
Academic and industry experience before Imperial
What work experience/internships did you have before beginning with Imperial College Business School?
Prior to joining Imperial, I had internships in various industries. I started to work for Industrial & Commercial Bank of China, which is one of the largest commercial banks in Asia. I then joined Nielsen as a Data Analyst intern, using quantitative methods to do market research for automotive clients like Mercedes and Volkswagen. After that, I interned at A.T. Kearney, a global-leading consulting firm, and worked on a strategic planning project for a Chinese state-owned chemical enterprise.
Why did you decide to study an MSc in Business Analytics and why specifically at Imperial College Business School?
We live in a data-oriented world now, which means business knowledge alone is not enough to make positive contributions for decision making. Hence, I decided to do MSc Business Analytics, as I believe it will help to combine my business acumen with advanced analytics skills. Imperial is special for me, because of its good reputation, its well-designed curriculum and the potential work opportunities it provides.
Studying MSc Business Analytics
What makes MSc Business Analytics at Imperial College Business School unique?
The MSc Business Analytics programme at Imperial College Business School provides a well-designed curriculum with core modules that can help to build solid foundations for analytics (programming like Python/R/SQL and basic understanding of data), while electives equip us with domain-specific knowledge. What’s more, Imperial focuses not only on academic study, but also gives students opportunities to put their analytical skills into practice. For example, students can be involved in a Data Spark project, where we do a data analytics consulting project for clients using real world data.
Which has been your favourite module so far and why?
My favourite module is Machine Learning, which is one of the most popular techniques in data-related industries. This module introduces some important algorithms such as Naïve Bayes and Tree Model to us. The content in this module is proven to be very useful when we take electives like Big Data in Finance and Advanced Machine Learning. What’s more, when interviewing for a data analyst job, the techniques covered in this module are frequently discussed.
Did you have a favourite professor/lecturer and why?
Dr Wolfram Wiesemann is my favourite lecturer. He leads the Optimisation and Decision Models module and the Machine Learning module, both of which are very important for Business Analytics students. Although the topics are challenging, Wolfram always finds the easiest way to explain complex problems to us.
What clubs, societies or other activities have you been involved in at Imperial?
I act as the academic leader for the Business Analytics programme. I collect feedback from students, and make academic-related recommendations to our faculty and programmes team. I enjoy this role, especially when I know my feedback will benefit teaching.
Opportunities from studying at Imperial
What has been the greatest opportunity you have had at Imperial that you wouldn’t get anywhere else?
The best opportunity is working for Imperial Business Analytics. At this institute, we can take part in the Data Spark project, in which students work as a consulting team to solve data problems. The project is special, because different from coursework, we get the opportunity to work for real world businesses. The Data Spark team analyses the data set as required to solve business problems, using knowledge we gained on the programme, to then present our findings to the clients. We communicate with clients on a weekly basis and get feedback from them, which helps to know how to solve practical issues with our analytical knowledge.
How have you benefited from being part of the wider Imperial College London community?
Being a part of the Imperial community means more career opportunities. First, you can join career fairs and meet with employers, from this, you gain first-hand insights about potential jobs. Also, you can build your career network by connecting with alumni. For example, I searched on LinkedIn and asked some alumni about interview tips for a specific company, this is helpful for my job seeking.
What are your future career goals and how have they been realised since being at Imperial?
I have discussed my career path with staff from the Career and Professional Development Service, and have decided to start my career in the technology industry as a data analyst. Most technology companies know the power of data, and they really love candidates with advanced data analytics skills.
Advice for future students
What advice would you give someone who was thinking about applying for the programme?
For every candidate, my suggestion is to show a genuine interest in data analytics, it is not necessary that you have done a sophisticated data project, but you should prove that you love using data to solve real world problem. Secondly, show your ability to work in a team and prove that you can work with a diverse group of people. Lastly to show your understanding of the Business Analytics programme at Imperial College Business School, why it is special, what you can gain from this programme and what you can contribute to your cohort.
Looking back to when you were applying for the programme, did you attend any of the programme information session online or on campus? Did you find these useful in the recruitment process?
Before my application, I attended on online information session. It was very rewarding and gave me lots of insights for application. I do suggest every applicant to attend at least one event. If you are in London or the UK, it is better to join a campus info session.