‘Academic Success is Largely a Matter of Making Self-Discipline a Habit in Year One’
Vladimir Averin is a fourth-year student at HSE ICEF. He was named the overall winner of the Econometrics Universiade 2023, an annual competition organised by Moscow State University, having come second in the competition last year. In 2023, Vladimir will start his PhD studies at Yale University (USA). In his interview, he talks about the benefits of studying at HSE University, why econometrics requires creativity, and how to win a scholarship from the Yale University Department of Statistics and Data Science.
Becoming a Top Student
Studying at ICEF is not easy, but if you don’t let yourself be lazy and apply yourself in learning the core subjects, then you are bound to succeed. That’s the first thing I realised when I became an ICEF student. My first two years were the most difficult—I made a lot of mistakes before I finally figured out the right learning strategy. What also helped me to succeed was the design of the curriculum itself: at ICEF, each new course builds on knowledge from earlier courses, so it is important to study hard in your first year. In my third year, I even managed to combine study with work. I was also able to compete in (and win) some academic competitions and attend career events.
I learned about the Econometrics Universiade when I was a third-year student and decided to compete. I won second place, an achievement that greatly increased my confidence. I developed a passion for data science—econometrics and data science are related fields—and I thought about entering more contests. One was the International Data Analysis Olympiad organised by HSE in cooperation with Yandex. It involved student teams from many universities. My team managed to get to the final, which was another challenging but rewarding experience for me.
It soon became my ambition to reach a high academic level. As a first-year student, I joined ICEF Academia, a programme that offers opportunities to study particular courses in greater depth. Based on the results of my first year (especially in mathematical analysis, in which I scored full marks), I earned a place in the Summer School of the London School of Economics. In my second year at ICEF Academia, I decided to go further and took a highly challenging course in statistics. It embraced topics as diverse as programming, matrix statistics, and stochastic analysis, and turned out to be a very interesting experience. I’m glad I took those extra courses.
I think that academic success is largely a matter of making self-discipline a habit as early as year one. But, of course, my passion for learning kept me going in the first place.
Gaining Research Experience
Research wasn’t my number one goal for the majority of my studies here. I was looking more to get the skills required in the workplace. At the same time, I knew that candidates with good research skills were seen by employers as capable of bringing more to the job. They also stand a better chance of getting tasked with more exciting roles. My current job involves a lot of research—I collect and analyse data, build hypotheses, and try to understand how one factor affects another. Even though I gained my research skills mostly in the workplace, not in a laboratory doing research projects, I think I have sufficient understanding of how applied academic research works.
In my third and fourth years, I worked as a research assistant under Vitalijs Jascisens (associate professor at ICEF between 2018 and 2022) and Ekaterina Kazakova (member of the class of 2015 and academic). As such, I took part in interesting projects that involved data collection and analysis. I learned how to set research tasks and solve them using data, and I gained experience with scientific methodologies and concepts. It was in my fourth year that I began to focus more on gaining academic experience. Most academic fields offer room for nearly limitless research. The deeper you go into detail exploring a phenomenon, the better you are prepared for quality research and the more competitive you become as a job candidate. This led me to start postgraduate studies.
ICEF offers a wide range of elective courses and activities designed for students to gain research experience. There are teaching seminars that present PhD programmes and research that is being conducted in various fields of economics and finance. These are very helpful, because they examine papers and theses from previous years and help students to write their own papers.
At HSE, it is easy to get support and feedback from teachers. Show initiative and be sure to formulate your research question clearly
The area I would like to explore scientifically in the future involves data analysis, statistics, and data science in general. I discovered this as early as my second year. I have always enjoyed working with data, doing statistical analysis to reach a conclusion, calculation or model.
Winning the Econometrics Universiade
At ICEF, we start to learn econometrics in our third year. I heard about the upcoming Universiade and decided to compete. I was curious to test my knowledge of Econometrics, data analysis and statistics, and to compete with other students. There are many different hackathons that test your knowledge of data science and programming skills, but very few that require in-depth knowledge of the theory. The Econometrics Universiade is special in this sense. Even though data science and econometrics are two related fields, the former uses a different approach which requires the ability to interpret computational results in addition to forecasting skills.
Econometrics competitions present interesting problems. They don’t require you to build sophisticated models; solutions are mostly built on interpretation and theoretical reasoning. Like all other courses, econometrics is taught at ICEF in English, so it took some time to interpret the problem and formulate the solution in Russian. I did not do any special preparation for the Universiade. I relied solely on what I’ve learned from ICEF’s strong course in Econometrics. Those who are looking to increase their econometrics skills can take courses on time series and panel data in their fourth year of study. But what also helped me win was my data analysis skills, knowledge of statistics, and the machine learning courses I did earlier.
This was my second win in the Econometrics Universiade. I was very curious to learn what problems the organisers had prepared for us this year, and it was an interesting experience discussing the solutions with the other contestants afterwards. I am glad I was able to win the top prize, especially because there were many strong contestants.
Data Science
My interest in data science and programming emerged later. I didn’t even know they offered nice career prospects before I became an ICEF student. Nor had I ever considered them as my future options.
It wasn’t until I actually started learning programming that I realised it wasn’t as difficult as I’d expected. Combined with statistical theory, the use of multiple programming languages for data interpretation has turned out to be the most exciting thing I ever learned
ICEF teaches Python and SQL as electives. I was pleasantly surprised to discover these two languages weren’t difficult at all to use, provided that you have enough practice. And I was greatly inspired by the career stories of ICEF graduates who chose to become data scientists. I see some really good career prospects here and I think I should become one too.
In addition to econometrics and machine learning, I took electives in data science and neural networks. Knowledge of these fields will help me decide on my future research track. I might choose to do applied research or go deeper into theory, statistical analysis and data interpretation, or go into an interdisciplinary area depending on my research tasks. I currently serve as a junior quantitative analyst at Raiffeisenbank, so I use data science every day. I would like to enhance my experience as a researcher and am planning to start a PhD at Yale University as a way towards a job where I’d be dealing with non-trivial research tasks on a daily basis.
Admission to Yale
To be honest, a PhD was my ‘just in case’ option, my Plan B. It wasn’t until I got the invitation from Yale University and discussed my prospects in the USA with teachers and friends that I made it my Plan A. I first decided to do a master’s in data science or statistics, but someone told me I could skip the master’s and go straight for PhD if I had a strong portfolio. I thought my research experience wasn’t strong enough for that, but I was wrong.
I gave my plan serious thought, studied the career tracks pursued by PhD holders, and realised that I didn’t have to stay in academia after earning my PhD. Many PhD holders end up in industry. Applying for a PhD is much more competitive than for a master’s. I got admitted to Yale and received a scholarship from its Department of Statistics and Data Science. I have five years of in-depth study of data science and new research ahead of me. I’ll have enough time to decide on what I want to do professionally and land a job exciting enough to keep me working on research tasks.
I have already met some of the teachers and presented my academic interests to them. They asked me why I wanted to do a PhD and gave details of my curriculum, how the learning process is arranged, and what extra courses I’d be able to take. It felt like I had the professors all to myself on that online open day. Yale also hosts many student events. I am looking forward to experiencing its vibrant environment, seeing the campus, satisfying my scientific curiosity and discovering lots of new things.