SQL • Python • Tableau • Power BI • Excel • Google Sheets
- 📊 Data & Business Analyst with a background in Physical Therapy and Retail
- 🧹 Skilled in data cleaning, preprocessing, exploratory data analysis (EDA), and business insight generation
- 🗄️ Experienced in SQL for KPI reporting, segmentation, trend analysis, and business intelligence
- 📈 Build interactive dashboards using Tableau and Power BI
- 🤖 Currently strengthening machine learning fundamentals, including regression, classification, A/B testing, and model evaluation
- 🚀 Experienced in delivering end-to-end analytics projects from raw data to stakeholder-ready dashboards
- 🌍 Open to Data Analyst and Business Analyst opportunities
| Category | Tools |
|---|---|
| 💻 Programming & Querying | SQL, Python |
| 📊 BI & Visualization | Tableau, Power BI |
| 📑 Spreadsheets | Excel |
| 🧠 Data Analysis & ML | Pandas, NumPy, Scikit-learn |
| 🗄️ Databases | MySQL, PostgreSQL |
| 📉 Visualization Libraries | Matplotlib, Seaborn |
| 📚 Additional Knowledge | R Basics |
End-to-end analytics project focused on identifying churn drivers, high-risk customer segments, and revenue loss impact.
Key Highlights
- Cleaned and transformed customer data using Python
- Performed SQL analysis to identify churn patterns and revenue impact
- Built Tableau dashboards to visualize customer behavior and churn risk
- Identified high-value customers at risk of churn and key churn drivers
- Quantified revenue impact associated with customer attrition
Tools: Python • SQL • Tableau • Pandas
Business-focused marketing analytics project analyzing 166K+ campaign records across three beauty retail brands to identify profitability drivers, channel effectiveness, customer segment performance, and optimization opportunities.
Key Highlights
- Performed Excel-based data cleaning and feature engineering
- Conducted SQL analysis across channels, campaign types, brands, and customer segments
- Built Tableau dashboards for KPI tracking and performance monitoring
- Identified high-performing audience-channel combinations and loss-making campaigns
- Delivered actionable recommendations for budget allocation and campaign optimization
Tools: Excel • MySQL • Tableau
End-to-end analytics project focused on sales performance, profitability, supplier evaluation, and inventory optimization.
Key Highlights
- Analyzed sales, profit, returns, and inventory performance metrics
- Evaluated supplier and store-level business performance
- Identified slow-moving, overstock-risk, and stockout-risk products
- Built Tableau dashboards to support inventory and profitability decisions
- Delivered recommendations to improve operational efficiency
Tools: Python • SQL • Tableau • Pandas • NumPy
📧 Email: adityapandey12391@gmail.com
💼 Open to Data Analyst and Business Analyst opportunities