Aleksei Mamchenko

I turn complex financial, operational, research, and market data into KPI reports, dashboards, and practical recommendations. My work combines SQL, Python, Power BI, Tableau, Excel, BigQuery, and strong research methodology.

At EPAM Systems, I processed large financial and regulatory datasets for machine learning applications, extracting structured insights from documents up to 1,300 pages while maintaining accuracy across multilingual data. At Remy Trade, I analyzed financial, customer, and operational data to identify performance trends, risks, and revenue anomalies for stakeholders.

At the International Institute of Genealogical Research, I design chatbot conversation architecture and AI evaluation methods, including testing for hallucinations, prompt injection, security, UX, and business logic. I also redesigned RAG knowledge-base practices around modular datasets, metadata, retrieval priorities, and governance standards.

My projects include movie analytics dashboards, a recommendation-engine pipeline using Python, APIs, BigQuery, and Power BI, Steam market investment analytics, and AI-powered job-application automation workflows. I bring a PhD in Social Psychology and a research-driven approach to statistical analysis, data quality, and analytical storytelling.