🎯 Aspiring Data Analyst | Python • SQL • Excel • Power BI
📊 Passionate about exploring data, finding insights, and creating clean visualizations.

• 📺 Netflix EDA – Exploratory Data Analysis of Netflix dataset.
• 🎥 YouTube Trending EDA – Analysis of trending videos across countries.
• 🏪 Superstore - Top-10 customers, AOV by category, monthly trend, region/segment profitability, ABC, discount impact.
• 🎵 Chinook - Monthly revenue & MoM, top customers, genre share, support-rep performance, basket, cohorts, RFM.
• 🎬 Sakila – Rentals KPIs: monthly revenue & MoM, top films/customers, staff performance, country breakdown, cohorts & RFM.
• 📊 Sales Analysis (pandas) – Retail sales EDA with Python (pandas, matplotlib, seaborn). Includes monthly sales trend, top products, regional profitability, and sales vs profit analysis.
• ☕ Coffee Chain Analysis – EDA of global coffee chain sales using Python (pandas, matplotlib, seaborn). Includes monthly sales trends, top products, category profitability, and sales vs profit correlation.
• 👥 Customer Segmentation – RFM Analysis – RFM-based customer segmentation using Python (pandas, matplotlib, seaborn). Identifies loyal, new, at-risk, and lost customers with visual insights and data-driven scoring.
• 💹 Crypto Market Analysis - Cryptocurrency market analysis using Python (pandas, matplotlib, seaborn) and the CoinGecko API.
  Includes price trends, volatility, trading volume, correlation matrix, and max drawdown analytics.
• 🧑‍💼 HR Analytics – Workforce insights using SQL (SQLite). Includes department-level salary analysis, gender ratio, hiring & termination trends, and experience-based pay insights.
• 💹 Finance Market Analytics - SQL + Python project for market data ETL and analytics. Uses yfinance to fetch stock prices, stores them in SQLite, and computes daily/monthly returns, top-performing months, and KPIs.
• 💳 Credit Card Fraud Detection (Deep Project) – End-to-end fraud detection project on extremely imbalanced data. Focuses on precision-recall metrics, PR-AUC, decision threshold tuning, and business cost trade-offs. Includes error analysis, false positive/false negative investigation, and executive-level recommendations.

📊 Data Analytics

• Python (pandas, numpy, matplotlib, seaborn)
• SQL (SQLite, joins, CTEs, window functions)
• Excel (Pivot Tables, VLOOKUP/XLOOKUP, Power Query)
• Power BI (data modeling, DAX basics, dashboards)
• Jupyter Notebooks
• Data Analysis: EDA, KPI tracking, cohort analysis, RFM, segmentation, data visualization

🎨 Frontend / UI Engineering

• JavaScript (ES6+)
• React (hooks, component-based architecture, state management basics)
• HTML5 / CSS3
• Responsive Design (Flexbox, CSS Grid)
• UI Development: reusable components, clean layouts, UX-oriented thinking
• Styling: Tailwind CSS

⚙️ Tooling & Workflow

• Git & GitHub
• VS Code
• npm
• Build Tools: Vite / Webpack (basic)
• API Integration (REST, JSON)

• 💼 [LinkedIn] https://www.linkedin.com/in/rufat-ahmad-zada-7084a319a/
• 📧 Email: rufat.ahmadzadeh@gmail.com

✨ Always learning, always exploring data!