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Hi 👋 My name is Rana Yalcinkaya

Business & Data Analyst

"Hello, I am a Business and Data Analyst with a background in Industrial Engineering. I have a passion for crafting narratives from complex datasets. I use SQL and Excel to manage datasets and leverage Tableau and PowerBI to convey my stories."

  • 📌 Click to see my Tableau Portfolio!

🚀 Technical Expertise

Programming Languages

  • Python

Python Packages

  • NumPy
  • Pandas
  • SciPy
  • Seaborn
  • Matplotlib
  • Statsmodels
  • Scikit-learn

Machine Learning Models

  • Regression (Linear, Logistic)
  • Naive Bayes
  • Decision Trees
  • Random Forest
  • AdaBoost
  • XGBoost

Integrated Data Analytics Stack

  • SQL
  • Excel
  • Tableau
  • PowerBI
  • Jupyter

📬 Let's Connect

I'm always eager to collaborate and discuss data-driven insights. Feel free to connect with me through the following channels:

Looking forward to engaging with the data community and tackling exciting challenges together!

Rana Yalcinkaya's Projects

hr_analytics-sql-tableau icon hr_analytics-sql-tableau

Using advanced SQL techniques and Tableau visualization, this project explores workforce dynamics, managerial structures, and potential salary disparities within an organization's employee database. A flexible SQL stored procedure enhances the analysis, fostering a data-driven approach to organizational insights.

salifort-motors-employee-retention icon salifort-motors-employee-retention

This project analyzes employee retention using machine learning models and explores factors affecting it, such as workload, job satisfaction, and salary disparities. The goal is to provide actionable insights for HR and management, aiding in the development of effective retention strategies.

selenium_web_scraper icon selenium_web_scraper

This project employed Selenium for web scraping on Glassdoor, extracting key job insights. The Python script, utilizing Pandas, dynamically navigated pages, extracting details. XPath usage, dynamic scraping, and Chrome options configuration streamlined the process.

waze-user-churn-binary-classification icon waze-user-churn-binary-classification

Applied advanced analytics to forecast Waze user churn, employing logistic regression, XGBoost, and comprehensive statistical analysis. Proficiently utilized Python, Scikit-learn, and StatsModels, demonstrating a keen ability to extract actionable insights.

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