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Machine Learning Methodologies for Evaluation Covid-19 Pandemic Impact on Employer’s Profiles on Employment Platform

Student: Marina Kravtsova

Supervisor: Liudmila Zhukova

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2021

Due to fundamental changes faced by modern world and rapid development of IT-industry new challenges for both employees, forcing them to be more flexible, and for companies, struggling for valuable personnel, appeared. Shift of working process to remote work, the refusal to rent office space, the refusal to hire interns who require training, allowed companies to reduce costs and greatly changed both: the labor market as a whole and the profile of each individual employer. This study aims to demonstrate how machine learning helps to solve complex problems giving instruments to evaluate the employer profile and demonstrate the changes that have resulted from the COVID-19 pandemic. For this study clustering approach was selected as a main one. The clustering problem is a fundamental problem of data analysis. Results of this research are to be: the collected database of employers vacancies during COVID-19 pandemic. Application of clustering method will help to build comparison of portraits of the employer before and after the pandeА mic. The final result is an analysis of how the pandemic has affected this employer portrait for the given vacancies.

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