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gsanaev/README.md

👋 Hi, I'm Golib Sanaev

Applied Data Scientist & Analyst | Python • SQL • ML • Analytics • Econometrics

Welcome to my GitHub!
I am an Applied Data Scientist and Analyst with a strong foundation in statistical modeling, data analysis, forecasting, and reproducible analytical workflows.
I combine PhD-level research experience with practical Python & SQL skills to build clear, interpretable, and well-structured data solutions that support decision-making.

I work extensively with Python (pandas, scikit-learn, OOP), SQL, Power BI, and modern analytical tools.
My interests lie at the intersection of Data Science, Applied Machine Learning, and Business Analytics.

🔧 Tools & Technologies

Languages & Analytics:
Python • R • SQL • Econometrics • Time Series • Forecasting • Regression & Classification

Python Stack:
pandas • numpy • scikit-learn • matplotlib • OOP • ETL Pipelines • APIs

R Stack:
dplyr • tidyr • purrr • ggplot2 • lubridate • renv • panel data workflows • economic indicator construction

Data Ops & Workflow:
Git • GitHub • Reproducible Analysis • Data Cleaning • Data Preparation

BI & Visualization:
Power BI • Tableau

Statistical Tools:
Stata • GLM • Model Evaluation • Feature Engineering • EDA

📁 Selected Projects

🔹 Business Data Integration & Economic Indicators Pipeline in R

A reproducible R-based workflow for integrating multi-source firm-level datasets, performing harmonization and validation, and generating sectoral & regional economic indicators.
Tech: R, dplyr, ggplot2, data cleaning, statistical integration, renv

🔹 Enterprise Financial KPI & Churn Analytics Platform

A modern finance analytics solution integrating data engineering, profitability modeling, and customer churn prediction — designed for banking and financial institutions.
Tech: Python, SQL, data engineering, PowerBI

🔹 ESG Classification Using Machine Learning

Supervised learning project building a transparent ML workflow to classify ESG indicators using feature engineering, model evaluation, and reproducible pipelines.
Tech: Python, pandas, scikit-learn, feature engineering, classification models

🔹 ESG Data Extraction Pipeline (APIs & Python OOP)

Modular, object-oriented pipeline for extracting ESG-related data using APIs, structured processing steps, and reusable components.
Tech: Python, OOP, APIs, ETL, data cleaning

🔹 Insurance Risk Modeling (GLM & Negative Binomial)

End-to-end actuarial risk modeling using GLMs to predict frequency, severity, and pure premium.
Tech: Python, GLM, Negative Binomial, model diagnostics, visualization

🔹 EU Hotel Demand Forecasting (Time Series)

Time series forecasting using SARIMA and feature engineering to evaluate tourism dynamics in European hotel markets.
Tech: Python, SARIMA, time series modeling, feature engineering

📌 Current Work

I am currently developing a Retail Data Intelligence project, combining:

  • Python OOP pipelines
  • DuckDB SQL modeling
  • API-based data extraction
  • Forecasting & clustering
  • Power BI dashboarding
  • Business-driven retail KPIs

Repository will be published soon.

📫 Contact

🔗 LinkedIn: https://www.linkedin.com/in/golib-sanaev
📧 Email: gsanaev80@gmail.com

Feel free to reach out — I am open to opportunities in Data Science, Applied ML, Data Analytics, and Business Analytics roles.

Pinned Loading

  1. business-data-integration business-data-integration Public

    A reproducible R pipeline for business data integration, quality checks, and economic indicator computation using synthetic firm-level datasets.

    R

  2. enterprise-financial-kpi-platform enterprise-financial-kpi-platform Public

    End-to-end financial analytics platform integrating synthetic data generation, DuckDB warehouse, profitability modeling, churn prediction, and Power BI executive dashboards.

    HTML

  3. esg-classification esg-classification Public

    A complete end-to-end framework for classifying corporate ESG performance using machine learning, SHAP, and interactive dashboards.

    Jupyter Notebook

  4. esg-llm-platform esg-llm-platform Public

    Hybrid ESG KPI extraction pipeline (regex + NLP + table parsing + optional LLM). Fully reproducible, schema-based, and tested on synthetic sustainability reports.

    Jupyter Notebook

  5. insurance-risk-modeling insurance-risk-modeling Public

    Actuarial data science with Python — GLMs, ML, and portfolio risk simulation

    Jupyter Notebook

  6. forecasting-explaining-hotel-demand-in-eu forecasting-explaining-hotel-demand-in-eu Public

    Forecasting and explaining hotel demand across EU countries (2015–2025) using econometrics and machine learning models, feature engineering, and data visualization in Python.

    Jupyter Notebook