About IDAO




Online Round

March 1-31, 2021

Online Finals

April 17-18, 2021




Higher School of Economics and Yandex are proud to announce the 4th International Data Analysis Olympiad.

The event is open to all teams and individuals, be they undergraduate, postgraduate or PhD students, company employees, researchers or new data scientists.

The event aims to bridge the gap between the all-increasing complexity of Machine Learning models and performance bottlenecks of the industry. The participants will strive not only to maximize the quality of their predictions but also to devise resource-efficient algorithms.

This will be a team machine learning competition, divided into two stages. The first stage will be online, open to all participants. The second stage will be the Online finals, in which the top 30 performing teams from the First Round will compete.

In 2018 the Online Round gathered 1533 participants from 55 countries. In 2019 the number jumped to 2187 teams from  78 countries. In 2020 the number grew further to 2756 participants from 83 countries. First two years the final took place in April at the Yandex office, Moscow. In 2020 due to the COVID-19 the Final was organized online. 

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There are two separate tracks during the online stage. From the machine learning perspective, the tracks will be similar, yet the restrictions put on the solutions are different for each track.

The first track will be a traditional data science competition. Having a labeled training data set, participants will be asked to make a prediction for the test data and submit their predictions to the leaderboard. In this track, participants can produce arbitrarily complex models. If you like to use 4-level stacking or deep neural networks, this is the right track for you – you will only need to submit test predictions. However, those who qualify for the finals will be asked to submit the full code of the solution for validation by the judges.

In real world problems, efficiency is as important as quality. Complex and resource-intensive solutions will not fit the strict time and space restrictions often imposed by an application. That is why in the second competition track, your task will be to solve the same problem as was in track one, but with tight restrictions on the time and on the memory. If you like the most efficient solutions, this is the right track for you.

We hope that the two tracks will make the olympiad fascinating for both machine learning competition experts and competitive programming masters, Kaggle winners and ACM champions, as well as everyone eager to solve real world problems with Data. Moreover, we encourage people with different backgrounds, ML and ACM, to team up and push Data Analysis to new frontiers.


30 teams best teams according to the Online Stage will be invited to the Final. First of all, we will ask the source code of your solution (for both tracks) which will be reviewed and validated. The solution must reproduce your submission exactly. Our experts will check that your solution contains no cheating, and your team does not attempt to unfairly pass the rules.
The finalists table 2021 will be published on April 1 only after the jury’s checking.

As part of the onsite round of the olympiad, speeches and workshops by international experts in machine learning and data analysis are also planned.


Dmitry Vetrov
Chairman of the Expert Commission,
Research Professor at HSE University,
Head of the Deep Learning
and Bayesian Methods Centre

Andrey Ustyuzhanin
Head of Methods for Big Data
Analysis Lab at HSE University

Evgeny Sokolov
Deputy Head of the Big Data
and Information Retrieval School,
HSE University

Aleksandr Pyatigorskiy
Vice-President, Director of
the Digital Department at Otkritie Bank

Nikita Kazeev
Junior Research Fellow, Methods for Big Data
Analysis Lab at HSE University

Davide Pinci
Istituto Nazionale di Fisica Nucleare -
INFN Sezione di Roma

Oleg Melnikov
Sr. Director of Data Science, ShareThis Inc.;
Adjunct Lecturer at Stanford University and UC Berkeley

Ilya Ivanitskiy
Team Lead at Avito, IDAO 2019 winner


Yandex is a technology company that builds intelligent products and services powered by machine learning. Our goal is to help consumers and businesses better navigate the online and offline world. Since 1997, we have delivered world-class, locally relevant search and information services. Additionally, we have developed market-leading on-demand transportation services, navigation products, and other mobile applications for millions of consumers across the globe. Yandex, which has 30 offices worldwide, has been listed on the NASDAQ since 2011.

Through its new educational initiative, Yandex will further advance its efforts to provide IT education and training to everyone. Yandex has committed to training 100 000 new specialists for the IT industry and 600 data analysis and machine learning experts over the next three years. Together with universities and institutions for professional development, Yandex will train 500 000 teachers in new educational technologies. The company’s educational platforms will prepare students for the most in-demand careers by equipping them with the skills they will need for the jobs of tomorrow. Yandex-trained graduates will also contribute to the advancement of data science and machine learning by applying their skills and expertise at institutions and private organizations around the world.


The Higher School of Economics (HSE) is the one of the most renowned Russian universities. The education is focused on economics and social sciences as well as high technologies and natural science. We stand on deep studying approach in fundamental disciplines combined with real experience at the biggest Russian companies to bring our graduates the perfect skills for their future carriers.

The HSE Faculty of Computer Science was created in March 2014 with the goal of becoming one of the world’s top 30 faculties in training developers and researchers in the field of big data storage and processing, system and software engineering and system programming. The Faculty is active in many research areas: machine learning, computer vision, theoretical computer science, algorithms for big data, optimisation, software engineering, and bioinformatics. We publish in leading computer science journals and present our results at major conferences.




Otkritie bank is one of top 10 major banks in Russia and a systemically important credit institution, which offers a full range of cutting-edge financial services to its corporate, retail, SMEs and Private banking clients. The single shareholder of Otkritie bank is the Central Bank of the Russian Federation with 100% interest in the share capital. In May 2018, the Supervisory Board of Otkritie bank approved its three-year business development strategy until the end of 2020. The key strategic target of the bank is to become the market leader providing excellent quick and convenient services to clients.

Otkritie bank operates through 579 offices in 241 cities located in 73 regions of the Russian Federation. Solid financial stability of the bank is proved by credit ratings assigned by domestic agencies ACRA (АА(RU)), RAEX (ruAA-) and NCR (AA+.ru), as well as international rating agency Moody’s (Ba2). Today, Otkritie is a large-scale financial group with a great potential for the further business growth. The companies of the group hold leading positions in the Russian financial market, such as Rosgosstrakh and Rosgosstrakh Life insurance companies, Otkritie Non-State Pension Fund, Otkritie Asset Management Company, Otkritie Broker, Baltic Leasing, and Customs Payment System.