Data Analyst · Product Analytics · Risk & Trading Analytics

I build practical analytics projects that turn raw data into clear business decisions:
data cleaning, SQL analysis, Python pipelines, dashboards, A/B testing, risk scoring, and trading performance analytics.

My portfolio combines two directions:

• Business & Product Analytics: data cleaning, SQL reporting, e-commerce funnels, A/B testing, dashboards.
• Risk & Trading Analytics: trader performance, anomaly detection, crypto trading journals, market signal evaluation.

• Data Analyst
• Product Analyst
• BI / Reporting Analyst
• Risk / Fraud Analyst
• Trading Data Analyst
• Freelance analytics projects

• Data Analyst: Python Data Cleaning, SQL Business Analysis
• Product Analyst: E-commerce Funnel Analytics & A/B Test
• Risk / Fraud Analyst: Trader Anomaly Detection
• Trading Data Analyst: BTC Indicator, Crypto Trading Journal Analytics
• Freelance Projects: Excel / Google Sheets Dashboards, Data Cleaning, SQL Reports, Trading Journals

End-to-end ML system for Bitcoin forecasting and trading signal delivery.
Includes feature engineering, walk-forward validation, model evaluation, Telegram bot delivery, FastAPI, RabbitMQ workers, SQLite WAL, Docker Compose, and explainable signal reports.

Python FastAPI CatBoost LightGBM Docker RabbitMQ SQLite Telegram Bot API ML Pipeline

Automated cleaning of a messy customer-order dataset using Python and pandas.
Standardized dates, emails, phones, city names, order statuses and revenue fields; removed duplicates; generated a clean CSV export and reusable data-quality report.

Python pandas matplotlib CSV Data Cleaning Data Quality

Business analytics project focused on SQL reporting and revenue/customer analysis.
Uses SQL queries to analyze customers, orders, products, revenue trends, top categories and business performance.

SQL SQLite DuckDB CTE Window Functions Business Analytics

Product analytics case study covering funnel conversion from visit to purchase and A/B test impact on final purchase conversion.
Includes uplift calculation, z-score, p-value and business recommendation.

Python pandas scipy A/B Testing Funnel Analytics Product Analytics

Risk analytics project for detecting suspicious trader behavior, coordinated account patterns and payout risk.
Builds an interpretable suspicious score with risk-tier segmentation and behavioral components.

Python SQL DuckDB Feature Engineering Risk Analytics Fraud Detection

Trading analytics dashboard for evaluating performance by symbol, setup, long/short direction, PnL, equity curve, win rate, drawdown and profit factor.

Python pandas Excel Trading Analytics Dashboard PnL Analysis

Languages & Data: Python, SQL
Python: pandas, NumPy, scikit-learn, scipy, matplotlib
Databases: SQLite, DuckDB, PostgreSQL
Analytics: A/B testing, funnel analysis, cohort logic, anomaly detection, trading metrics
Dashboards: Excel, Google Sheets, visual reports
Engineering: FastAPI, Redis, RabbitMQ, Docker, Git/GitHub
Domains: E-commerce, product analytics, crypto/trading analytics, risk/fraud analytics

• Data cleaning and data-quality reporting
• SQL-based business analysis
• Product funnels and A/B testing
• Trading performance analytics
• Risk scoring and anomaly detection
• Crypto trading journal dashboards
• ML pipelines for financial time series

• Russian — native
• English — technical documentation, written communication