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.

Technical skills

Python• Middle • 3y+
SQL• Middle • 3y+
Databases
PostgreSQL• 3y+
AI/ML
CatBoost• 3y+
LightGBM• 3y+
LLM• 3y+
NumPy• 3y+
RAG• 3y+
SHAP• 3y+
DevOps
Git• 3y+

Timeline

ML Engineer / Data Scientist Middle
TYMY Full-Time
Jan 2023 to Mar 2026 3 Years 2 Months Moscow Remote/Hybrid
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
Moscow, Russia