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gsanaev/README.md

👋 Hi, I'm Golib Sanaev

Data Analyst & Applied Data Scientist | Econometrics • Statistical Modelling • Enterprise Statistics

Welcome to my GitHub!

I am a Data Analyst and Applied Data Scientist with a strong foundation in econometrics, statistical modelling, data analysis, forecasting, and reproducible analytical workflows.

I combine PhD-level research experience with practical skills in Python, R, SQL, and statistical software to build transparent, interpretable, and well-structured analytical solutions that support evidence-based decision-making.

My work spans Data Science, Econometrics, Enterprise Statistics, Data Integration, and Business Analytics, with a particular interest in transforming complex data into meaningful statistical and analytical insights.

I work extensively with Python, R, SQL, Power BI, and modern analytical tools across a range of methodological and applied projects.

🎯 Areas of Interest

  • Data Science
  • Econometrics
  • Enterprise Statistics
  • Statistical Modelling
  • Data Integration
  • Business Analytics
  • Reproducible Analytical Workflows

🔧 Tools & Technologies

Languages & Analytics:
Python • R • SQL • Econometrics • Statistical Modelling • Time Series • Forecasting

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 Workflows • Data Cleaning • Data Preparation

BI & Visualization:
Power BI • Tableau

Statistical Tools:
Stata • GLM • Statistical Inference • Model Evaluation • EDA

📁 Selected Projects

🔹 Multisource Enterprise Statistics Integration Workflow in R

A reproducible methodological workflow demonstrating statistical editing, harmonization, multisource integration, and structural indicator production using synthetic enterprise data.

Tech: R, dplyr, statistical validation, harmonization, data integration, reproducible workflows, 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, Data Analytics, Enterprise Statistics, Applied Econometrics, 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 1

  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