Python/Go • Distributed systems • Firebird DB tools BI platforms | Quantum mechanics | Karting → making computers go fast
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
voice-to-text
January 19, 2026 – Present
Bulk voice message transcription using Whisper. Telegram, WhatsApp, batch processing, CLI & Python API
View Projectgo-audio-converter
January 13, 2026 – Present
Pure Go audio converter — no ffmpeg, no CGO. Convert WAV, FLAC, OGG to MP3. Single binary, works everywhere.
View Projectigaming-platform
January 12, 2026 – Present
iGaming Platform Core — Wallet Service, Bonus Engine & ML-powered Fraud Detection. Go + gRPC + PostgreSQL + Redis + RabbitMQ. Production-ready microservices for online casino/betting.
View Projectaudiobook-cleaner
December 30, 2025 – Present
Clean audiobooks from background music and noise using MDX-Net/Roformer AI models. Handles large files with automatic chunking.
View Projectarchive_labels
October 15, 2025 – October 15, 2025
Генератор этикеток для домашнего архива на Python
View Projectmusic_recognition
September 5, 2023 – Present
Bulk music recognition & tagging tool. Identify unknown MP3s and organize your music library automatically.
View ProjectFirebirdRepairBase
October 24, 2016 – Present
Low-level Firebird Database Analysis and Recovery Tool (Pascal/Delphi).
View ProjectXlsForXMLHttp
December 17, 2015 – March 13, 2020
Program on golang for converted from xls files to xml on http server
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong initiative and self-driven learning, which can be a positive cultural fit. The diversity of projects, from audio processing to iGaming platforms, suggests adaptability and a broad interest in technology. However, the target role is 'Data Scientist', and while there are relevant projects, a significant portion of the portfolio is focused on Go and low-level system development, which might indicate a broader engineering interest rather than a focused data science passion. The lack of team-based projects makes it difficult to assess collaboration fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.