Arailym Azatkyzy

Developed an interactive Power BI dashboard based on a real-world dataset from People Consulting to analyze the IT and Digital labor market in Kazakhstan. Processed and visualized survey responses from 1,111+ IT professionals, identifying key employer branding metrics and brand awareness levels. Visualized "Net Attractiveness" and candidate decision-making factors for top tech companies, including Yandex Qazaqstan, Kolesa Group, and InDrive. Engineered dynamic filters to compare preferences across IT specialties such as Data Science, Analytics, and Machine Learning.

Developed an interactive web application to extract and analyze Reddit discussions using Python, Reddit API, and Streamlit. Implemented Aspect-Based Sentiment Analysis and advanced text clustering (SentenceTransformers, UMAP, HDBSCAN) for precise topic extraction, bypassing baseline keyword methods. Engineered a custom polarization metric using KMeans and silhouette scores to mathematically quantify user controversy and consensus. Visualized sentiment trends and text analytics using Plotly, delivering original, ML-driven insights without relying on LLM-generated summaries. Tech Stack: Python, Pandas, Scikit-Learn, Streamlit, Plotly, NLTK, TextBlob.

Engineered an interactive, Duolingo-inspired web application for learning American Sign Language using Python and Streamlit. Trained a custom Multilayer Perceptron (MLP) classification model on a manually collected dataset of 10,800 hand gesture images, utilizing MediaPipe for precise hand-landmark extraction. Deployed live video processing via WebRTC, enabling low-latency, real-time gesture prediction and dynamic user feedback directly in the browser. Developed complex session state management to support multiple gamified modules (Lessons, Timed Challenges, Word Spelling) with XP, streaks, and progression tracking. Tech Stack: Python, MediaPipe, Scikit-Learn, Streamlit, WebRTC.

Designed and implemented a production-ready relational database from scratch with a normalized 3NF architecture comprising 20 distinct tables and many-to-many bridge entities. Populated and managed a high-volume dataset of 100,000+ records using Mockaroo to simulate a realistic production environment for performance testing. Developed 28 advanced PL/SQL blocks, including optimized cursors, packages, audit log triggers, and collections (BULK COLLECT) to enforce business logic at the database level. Built a unified, single-page administrative CRUD interface using Oracle APEX with dynamic routing and safe Popup LOVs for managing foreign key relationships.