I'm a Data Scientist and AI Engineer focused on transforming data and machine-learning models into practical, end-to-end intelligent systems. My expertise covers the complete project lifecycle, including data collection and preprocessing, exploratory data analysis, visualization, feature engineering, model development, evaluation, API integration, and deployment.

I have hands-on experience in Machine Learning, Natural Language Processing, LLM applications, Retrieval-Augmented Generation, semantic search, vector embeddings, and AI Agent workflows. I combine strong data-science foundations with backend engineering skills using Python, SQL, FastAPI, PostgreSQL, and Docker, enabling me to build solutions that go beyond experimental notebooks and become usable, deployment-ready products.

One of my key strengths is the ability to connect multiple technical layers within a single solution: extracting meaningful insights from data, developing and evaluating predictive models, integrating modern generative AI technologies, and exposing these capabilities through scalable APIs and user-facing applications. I’m particularly interested in building reliable AI systems that support real-world decision-making through accurate predictions, grounded responses, explainability, and clear data visualization.

Core strengths: Data Analysis and Visualization, Machine Learning, NLP, LLMs, RAG Systems, AI Agents, Semantic Search, Model Evaluation, FastAPI Development, and End-to-End AI Solution Engineering.