Egor Kulapin
ML Engineer
Python
SQL
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Overview
Technical skills
Timeline
Roles
Overview
Machine learning engineer and data scientist working on production ML systems for fintech SaaS. Builds tabular ML models for lead/agent scoring, antifraud, and churn/attrition prediction, and develops LLM/RAG solutions with hybrid retrieval and evaluation. Focuses on validating models with business-impact metrics such as conversion, retention, and loss reduction.
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Technical skills
Python
SQL
AI/ML
LLM
NumPy
CatBoost
LightGBM
SHAP
RAG
Databases
PostgreSQL
DevOps
Git
Timeline
ML Engineer / Data Scientist
•
Middle
TYMY
•
Full-Time
Built ML models for agent scoring to prioritize leads for banking throughput, including time-based validation, class imbalance handling, and model interpretability with SHAP. Developed an LLM-powered RAG assistant using hybrid retrieval (vector + BM25) with reranking, document chunking, and answer quality evaluation. Implemented antifraud detection for applications sent to banks using anomaly detection and fraud-specific validation, and created churn/attrition models to identify agents likely to stop generating leads.
CatBoost
LightGBM
LLM
RAG
SHAP
PostgreSQL
Python
NumPy
Git
SQL
National Research University Higher School of Economics
Bachelor's Degree