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nkrivoshey/README.md

Hi there 


👨‍💻 About Me

Middle Data Analyst & Data Scientist with 4+ years of experience transforming data into strategic impact:

At Metropolitan Premium Properties (03/2024 – Present)

  • 90% productivity boost through Python/GCP reporting automation.
  • Developed a Telegram bot for real-time Dubai market analytics & ML-powered price forecasts across 80+ locations.
  • Built a 2-year workforce & revenue forecasting model to optimize headcount planning.
  • Unified data from PropCRM, Bitrix24 & 1C into a centralized database for seamless ETL.
  • Created a Marketing ROI Power BI dashboard driving a 10% revenue uplift.
  • Automated front-desk data entry via Apps Script, accelerating collection by 80%.

At Sberbank (02/2022 – 03/2024)

  • Detected 1.5 M+ compliance violations using Python & SQL, mitigating legal risk.
  • Trained ML classifiers (Random Forest, XGBoost) to flag 300 K critical bankruptcy-related cases.
  • Applied graph-based process mining to expose 1 M systemic delays.
  • Implemented NLP pipelines (PyMorphy2, NLTK) to structure client documents, cutting processing time by 70%.
  • Built scalable ETL/ELT pipelines with PySpark & Hadoop, improving data consistency.

🛠️ Tech Stack

  • Languages: Python, SQL, R, C++, Java
  • ML & NLP: scikit-learn, XGBoost, PyTorch, Transformers, NLTK, PyMorphy2
  • Data Engineering: PySpark, BigQuery, Hadoop (Hive/YARN), Airflow, ETL/ELT
  • BI & Visualization: Power BI (DAX, Power Query), Tableau, Pandas, NumPy, Matplotlib, Plotly
  • Cloud & DevOps: GCP, AWS, Docker, Linux, Git

🚀 Selected Projects

  • Real-Estate Analytics Bot (2024–Present)
    Python & GCP-powered Telegram bot delivering live dashboards and ML price forecasts for 80+ Dubai areas.
  • Workforce & Revenue Forecasting (2024)
    2-year predictive model in Python, aligning hiring with revenue goals.
  • Compliance Violation Detection (Sberbank, 2022–2024)
    NLP & ML pipelines that flagged 1.5 M+ violations and accelerated legal case processing.
  • EKF Optimization (2025)
    C++ implementation of Extended Kalman Filter using BFGS/L-BFGS for faster matrix inversion.
  • Mutual Funds Performance Study (2021–2025)
    Econometric analysis (CAPM, Carhart, Treynor–Mazuy, clustering); results requested by NAUFOR & Central Bank.

🎓 Certifications & Awards

  • Speaker, RANEPA Open Scientific Seminar (July 2025)
  • Finalist, Yandex Olympiad “I am a Professional” (Economics & Math)
  • DataCamp & Stepik: Supervised Learning, Time Series, Advanced SQL

🤝 Let’s Connect

📬 [email protected]
📱 Telegram
🔗 LinkedIn

Pinned Loading

  1. Pet-Projects Pet-Projects Public

    My personal pet projects that will be useful for anyone who wants or already works in the fields of DA/DS/DE

    Jupyter Notebook 1

  2. SBER_TASK_Multiclassing_of_passwords SBER_TASK_Multiclassing_of_passwords Public

    Here you can find pipeline for solving multiclassing task by Sberbank

    Jupyter Notebook

  3. Introduction_PyTorch Introduction_PyTorch Public

    Introduction to PyTorch

    Jupyter Notebook 1

  4. PyTorch_Classification_Images PyTorch_Classification_Images Public

    This is where I solved the task of the classification of images with PyTorch

    Jupyter Notebook 1

  5. Car_price_prediction Car_price_prediction Public

    ML task for predicting car prices.You can use my code for training

    Jupyter Notebook

  6. Diamond_price_prediction Diamond_price_prediction Public

    ML task to predict the price of diamonds.You can use my code for training

    Jupyter Notebook