Burxoniddin Botirov

I’m a data-focused Economics & Data Science student (expected May 2027), building a foundation in data structures, machine learning, econometrics, databases, and statistics while specializing through hands-on programs.

As a Data Engineer at Urban Lab, I architect ETL pipelines to extract, transform, and load data from heterogeneous sources into a corporate data warehouse. I also elicit and formalize system requirements for relational databases and enterprise data warehousing, and I’ve engineered and deployed supervised ML classification models with reliability standards. I’m actively researching and prototyping reinforcement learning algorithms for autonomous decision-making applications.

Previously, as a Data Analytics Intern at Uzcard — National Payment System of Uzbekistan, I completed a structured Python data analytics program and worked with large-scale financial datasets to clean, explore, and visualize insights for operational decisions. I built reusable analytical pipelines that reduced manual processing time across recurring payment analytics workflows.

My projects reflect a production mindset: a Credit Scoring ML Engineering System with PostgreSQL, Airflow DAG orchestration, MLflow tracking, XGBoost, FastAPI scoring, Kafka streaming, ClickHouse feature store, and Docker Compose—covering feature engineering, training, Optuna hyperparameter optimization, deployment, and real-time inference. I also developed a Revenue Analytics Dashboard in Power BI and SQL/Python to support executive decision-making for 50+ stakeholders.