“After completing my exchange program in 2016-2017 Term 2, I immediately joined UBS AG as their summer intern in Group Operations.
During the internship, I was given an ample amount of work within my team such that I could be really involved with the team and the firm, as well as learn the most – technically and personally – out of those ten weeks.
From this internship, and based on what I have learnt from the GLEF curriculum, I gained much greater understanding of the global financial markets, as I had had hands-on experience in dealing with the real-life operation of the banking industry, and also the opportunity to work with teams from various regions over the world.

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“I worked in the Revenue Management Team of Phone Banking Department, which is responsible for evaluating and driving the performance of frontline staff. During my 6-month internship, I had worked on different analyses under the coaching of managers and colleagues, such as a funnel analysis investigating the root cause of underperformance. The internship experience was very fruitful as it equipped me with both technical and soft skills of the industry.

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“In the first term of 2017 I was offered an internship with the Valuation Team of Deals Advisory at PricewaterhouseCoopers. During my internship, I was given the chance to involve in multiple tasks, which were related to the valuation of different financial assets. I have been able to apply my textbook knowledge I acquired from the courses in university. GLEF provides ample resources to support students to develop skill sets that are practical in business, as well as many chances to participate in internship.

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“After I returned from my exchange study in US, I started immediately with my job at State Street working as a FX Trading intern.

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“I was at MarcPoint, a big data technology corporation providing digital marketing consultancy, as an Algorithm/Data Mining engineer in 2016, responsible for developing the similar product classification system.
MarcPoint initiated the project due to the increasing interest from many vendors on Taobao to understand the current market and its competitors.
The algorithm is implemented with three stages including learning low-dimensional data representation, calculating distances between items and training model ensembles.

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