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Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Shark

Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Shark

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ourharlequin/README.md

👋 Hi, I am Budimir Voroshilov

💼 Full Stack Data Analyst | Data Scientist | AI agents developer
🌍 International experience (Serbia and Georgia) 📊 Specialized in advanced data analysis with Python, SQL, Power BI, Databricks.

🚀I am

Data Analyst with over five years of experience. I specialize in marketing and product analytics, business consulting based on data-driven decisions. There are a lot of tools that I usually use in my working routine: SQL queries, DBT service, ETL/ELT pipelines to collect data from data-lakes or data-warehouses, GA4 with GTM to get events from websites, Python with different libraries for data preparation, automatization, researches, ML model building, BI tools for data visualization (the dashboards) like Tableau, PowerBI, SuperSet, Redash, Databrikcs, Grafana. I also have exp with mathematical statistics features, AB tests and non-AB tests methodologies (cohort analysis, sequential tests, DiD etc).

🛠️ Technologies and Tools

  • Languages: Python, SQL, PySpark, C++, VB script
  • Data Analytics: Pandas, NumPy, Seaborn, Matplotlib, Requests, Statsmodels, Sklearn, TensorFlow, PyTorch, Sqlite3, Plotly, Appsflyer
  • BI Tools: Tableau, PowerBI, SuperSet, Redash, Databrikcs, Grafana
  • Databases: PostgreSQL, ClickHouse
  • Cloud: AWS, GCP

📚 EDUCATION

🎓 Master's Degree in Product marketing and Data analysis – ITMO University (GPA: 4.85)

🌐 Contacts

📩 Email: ourharlequin@gmail.com
🔗 LinkedIn: www.linkedin.com/in/budeshka 🔗 Telegram: https://t.me/budeshka 💻 GitHub: github.com/ourharlequin

✨ Passionate in business consulting based on data-driven decisions.

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  1. Crypto_balances_checkup Crypto_balances_checkup Public

    I reconciled user balances for BTC, ETH, and USDT by comparing ending balances with the net effect of deposits, withdrawals, and trades over the last 30 days

    Jupyter Notebook

  2. DiD_Gamedev DiD_Gamedev Public

    The notebook file contains battles data for two groups of players divided by availability of some changes in setting and configuration in the game.

    Jupyter Notebook

  3. Marketing_analysis Marketing_analysis Public

    This project provides a comprehensive analysis of marketing campaign efficiency using Python and the Pandas library. The goal is to evaluate the acquisition costs versus the revenue generated acros…

    Jupyter Notebook

  4. Marketing_channels_analysis Marketing_channels_analysis Public

    This project is a comprehensive analysis of marketing lead quality, evaluating the alignment between two different scoring systems across major acquisition channels (Meta and Google Ads). The goal …

    Jupyter Notebook

  5. Marketing_cohorts Marketing_cohorts Public

    This project focuses on calculating unit economics and conducting cohort analysis for a trading app launched in Brazil in January 2023.

    Jupyter Notebook

  6. Time_Series_Research Time_Series_Research Public

    An end-to-end time series analysis and forecasting project designed to predict Daily Active Users (DAU) using historical data

    Jupyter Notebook