Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 1

Know how to:

•download, process, analyze and interpret data;
• use Python libraries for data processing and visualization, NumPy, Pandas, MatPlotLib, Seaborn, Plotly etc.;
   
• build and test statistical hypotheses;
• classify and cluster data;
• selection of features and construction of machine learning models;
• build linear and polynomial regression for forecasting;
• evaluate the quality of work of constructed algorithms;
• build decision trees and ensembles for task classification and forecasting.
Junior Specialist at Corporate Credit Analysis Department,  Kyiv July 2021 – Present, 1 year 11 mos.
• Received, cleaned, and prepared data using Excel for weekly and monthly reports, ensuring data integrity and reliability through data checks and cleaning. Created visualizations using PowerPoint to present results in a clear and concise manner.
• Responded to ad-hoc requests from the Head of Department, conducting data research, collection, cleaning, and analysis.
• Suggested changes to reporting indicators used to measure the unit’s effectiveness, which were implemented and resulted in improved accuracy in measuring team performance.
• Conducted analysis of financial statements for corporate clients, including simple market research from web sources.
• Detail oriented/self-motivated with the ability to learn and deploy new technology quickly