Position: Data Analyst
Category: Data Analyst
English level: upper
Years of experience: 0

Participated with a team of students in the hackathon where we developed a model for comment classification from IMDB. We have used sklearn as the main ML library; pandas, NumPy for data preprocessing, and nltk for natural language processing.

Completed Basics of Statistics (1, 2 part) course on Stepik. Learned basic methods and principles of statistical analysis, interpretation, and visualization of the results.

Completed a few ML-related courses on Coursera. Such as Machine Learning by Stanford University and Neural Networks by DeepLearning.ai. Where we have implemented a lot of models from scratch and learned some optimization technics.
Working freelance I have made website analytics, where I imported data from Google Analytics to Tableau and performed traffic source analysis, target audience analysis, and built a sales funnel.

As a python developer, I have created a few telegram bots for automation tasks. Such as a bot for searching for last-minute tours and getting updates every day, a bot for simplified car insurance, bot for getting insurance on your trip. Also, I have made a lot of web scrapers of different complexity. For these tasks, I have used libraries such as pandas, NumPy, beautiful soup, and selenium. And API's such as TelegramBotAPI, Twyton, facebook-sdk, EWA.

Also, I have collected and preprocessed a dataset with people who wear glasses. Photos were collected from Google Pictures with selenium and preprocessed by augmentation with the cv2 library.

Except for the projects I mentioned above I have written a matrix decomposition program from scratch on C as my course project. The program performs a LU, QR, and Cholesky decomposition for a given matrix.