I am passionate about turning data into meaningful insights and decisions. My work lies at the intersection of Business Analytics, Data Science, and Problem Solving, with a growing interest in building intelligent solutions that combine technology and strategy.
- Final-year engineering student with a strong analytical foundation
- Actively upskilling in Business Analytics, Data Science, and Machine Learning
- Enthusiastic about data-driven decision-making and problem-solving
- Interested in roles across Business Analytics, Product, and Strategy
- Programming & Scripting: Python, SQL, R, C, VBA
- Analytics & Visualization: Power BI, Tableau, Excel, Google Data Studio
- Machine Learning: Scikit-learn, TensorFlow, Keras, XGBoost, Pandas, NumPy, Matplotlib, Seaborn
- Databases: MySQL, PostgreSQL, MongoDB, SQL Server
- Tools & Platforms: Jupyter, Git, Google Analytics, Databricks, GCP, Azure, AWS
- Key Concepts: NLP, Deep Learning, Time Series, Data Cleaning, Statistical Analysis, Feature Engineering
- Strengthening expertise in Business Analytics and Machine Learning
- Applying skills through live projects across industries
- Preparing for data-focused roles in leading tech and consulting firms
- Exploring practical applications of AI in business decision-making
| Project | Description |
|---|---|
| Customer Churn Prediction | Developed a machine learning model to identify customers likely to churn in the telecom sector |
| Financial Performance Dashboard | Built an interactive dashboard to visualize KPIs and profitability trends |
| Fraud Detection System | Designed classification models to detect fraudulent transactions in banking |
| Market Research for Startups | Conducted competitor and user research for an early-stage startup |
| Product Pricing Strategy | Analyzed pricing data to develop a strategy for new market entry |
Additional projects are available in my repositories.
"Data tells the story. I help decode it."