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IDCidna-library
December 17, 2025 – December 20, 2025
IDCidna-library — GitHub repository
View Projectsocial_analyzer
December 17, 2025 – December 18, 2025
social_analyzer is a Python package for generating, simulating, and analyzing logically consistent social media content based on gaming and esports contexts.
View ProjectData-Storm
December 17, 2025 – December 19, 2025
Data Storm: A modular Python package for automated weather data fetching, cleaning, and statistical analysis using the OpenWeatherMap API and Pandas.
View ProjectEDA-CDA-SPL-Project
November 22, 2025 – December 17, 2025
Design and development of a Python package for conducting EDA with hypotheses/CDA
View ProjectAutoformula
November 9, 2025 – December 16, 2025
AutoFormula is an intelligent feature engineering framework for automatic analysis, generation, and evolution of dataset features.
View ProjectFake_News_Detector_for_Telegram_channels
April 28, 2025 – June 7, 2025
The Fake News Detector is a hybrid machine learning model for classifying false news texts from Telegram channels in Ukrainian, russian, and English. It combines TF-IDF, IBM Granite text embeddings, and logistic regression to detect disinformation in multilingual written content.
View Projectpython_stat_tests_visualisation
November 25, 2024 – November 25, 2024
Python-based library for automatic statistical hypothesis testing and visualisation of results. It selects appropriate tests based on data properties and supports intuitive analysis using t-tests, ANOVA, and other methods with visual outputs like histograms, Q-Q plots, and boxplots.
View Projectloredart_tensor
February 8, 2023 – September 28, 2025
A Dart-pure package for manipulation with tensors (multidimensional arrays of data) inspired by the TensorFlow API.
View Projectloredart_nn
February 6, 2022 – September 29, 2025
Simple library for creating and training Deep Neural Networks, written in pure Dart
View ProjectCultural Fit Analysis
The candidate shows a strong inclination towards independent research and development, as evidenced by numerous personal projects. The projects are diverse within the data science domain, covering areas like feature engineering, statistical analysis, NLP, and deep learning. This breadth of interest aligns well with a role that encourages exploration and innovation. However, the lack of team-based projects or professional experience makes it challenging to fully assess cultural fit in a collaborative environment.
Soft Skills & Operational Fit
The candidate's extensive personal projects suggest strong self-motivation, initiative, and a passion for data science. The descriptions indicate an ability to conceptualize and execute complex technical ideas independently. However, without formal work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or communication in a professional setting.