‘The Future of Consulting Lies in Data Analysis Projects’
First-year ICEF master’s student Tamara Shangina has won the McKinsey Moscow Next Generation Women Leadership Award 2017 with her project on data analysis. Below, Tamara discusses how she decided to switch gears from programming to finance, as well as what role case championships and a student loan from Sberbank have played in her life.
Case Championships Draw You In!
In my third year of undergrad, my classmate invited me to participate in a case championship. I agreed, but it was more about the team really. I learned what consulting was really during the case championship, and it made a strong impression on me. Almost immediately after, I was asked to participate in another championship and then another after that. Throughout the following year I continued participating in different championships and gradually started realising that I was drawn more to consulting than to programming. After my fourth year, I interned at PwC (a Big Four consulting and auditing company) and decided to continue my studies in a master’s programme in economics. I was deciding between the New Economic School and ICEF, but after looking at the academic plans, teaching staff, graduate perspectives, and all the support offered to students, I selected ICEF. I wasn’t able to get a government-sponsored spot, so I had to take out a student loan from Sberbank, which I definitely don’t regret doing. Now, after my first year of studying, I understand that I’ll more than just recoup these funds thanks to the new knowledge, projects, and prospects that have opened up for me.
For example, the majority of applications I sent out to consulting companies when I was an undergrad were rejected, whereas this year I am going through the selection process at a number of leading international consulting firms.
How to Master Economics with a Mathematics Background
There are different kinds of maths. I don’t have difficulty calculating something, but I have to read a large amount of literature and spend a lot of effort on understanding the economic significance behind all of these numbers and why, for example, some economic models are viable while some are not.
At first, English was also difficult. I didn’t have very good technical English before, and everything here is taught completely in a foreign language. You have to read, listen to lectures, and write in English. But after a few months of hard work, everything came together.
The McKinsey Next Generation Women Leadership Award 2017 is a competition held for girls by McKinsey’s Moscow office. The competition took place in three stages – a resume screening, a statement of purpose review, and two in-person interviews with HR and a McKinsey consultant. The last of the interviews included case studies, which was unexpected, but interesting. As the winner, I received a scholarship and mentorship from McKinsey, as well as access to different closed events.
I won with a project in which I analysed data from a chain of medical clinics. We are working on the project as part of the Centre for Mathematical Finance, which now has its own divisions at HSE and Moscow State University. Medical clinics have huge databases, but they are not used in any way. We used the data to build a client portrait, and we showed which groups of patients bring in more revenue. In addition, we demonstrated how client flow has changed both qualitatively and quantitatively over the last several years.
I want to promote data analysis among the masses. This seems like a prospective area. Most companies now have the technical capabilities to collect data, but they don’t always understand what to do with it. Before I began taking part in case championships and studying economics, I only knew how to process data, but I didn’t understand how to apply this to a company’s needs.
Now that I’ve worked with data, I’m able to predict different things, such as what will happen at a certain company or store depending on the season, region in which the store is located, and other important factors. I am also able to predict how to adapt an advertisement for the end consumer, as well as which advertising approaches are worth spending money on or not, and a lot more.
Lyudmila Mezentseva, HSE News Service
The Higher School of Economics has joined the LHCb collaboration at the Large Hadron Collider, which is operated by the European Organization for Nuclear Research. The group from HSE will consist of researchers from the Laboratory of Methods for Big Data Analysis (LAMBDA). This will give HSE researchers full access to data from the collaboration and allow the university to participate in various projects.
The joint department with SAS at the HSE Faculty of Computer Science aims to support educational programmes in data analysis and enrich teaching and learning with business expertise. The Higher School of Economics is the first Russian university to have founded a joint department with SAS.
On April 4, the winners of the First International Data Analysis Olympiad (IDAO) were announced. The event was organized by the HSE Faculty of Computer Science, Yandex, and Harbour.Space University (Barcelona) with the support of Sberbank. Magic City team from St. Petersburg took out first prize, a team from the Ukraine came second, and the Apex team from Belarus came third.
On February 20, the first online stage of the International Data Analysis Olympiad (IDAO) was completed. IDAO was organised by the Faculty of Computer Science of the Higher School of Economics in partnership with Harbour.Space University (Barcelona), Yandex and with the Gold sponsor, Sberbank.
The IDAO (International Data Analysis Olympiad), created by leading experts in data analysis for their future colleagues, aims to bring together analysts, scientists, professionals, and junior researchers from all over the world on a single platform. This is the first time an event of this scale will be held in Russia. The HSE Faculty of Computer Science, Yandex and Harbour. Space University organize the Olympiad with the support of Sberbank.
Concept lattices can help spot pedophiles on the web. Researchers of the HSE's Department of Data Analysis and Artificial Intelligence have helped the Dutch police create a computer program that can detect internet pedophiles and even determine how dangerous they can be.
The 4th Summer School of the Laboratory for Comparative Social Research (LCSR) was centered around Categorical Data Analysis and saw the participation of more than 40 junior academics from universities and research centres of Russia, Ukraine, Belarus, Italy, Germany, Poland, Romania, Israel and the U.S.