- Passionate Data Scientist with strong foundations in Machine Learning, Business Analytics, and Statistical Modeling.
- Experienced in analyzing real-world business data across Finance, Marketing, Retail, and Risk Analytics.
- I love turning complex data into actionable insights, dashboards, and predictive models.
| No. | Project | Domain | Description |
|---|---|---|---|
| 1️⃣ | Default Prediction & Stock Risk Analysis (Using Python) | Finance | Predicts company default risk and analyzes market volatility using ML and financial metrics. |
| 2️⃣ | Cafe Sales – Market Basket Analysis (Using Python & KNIME) | Retail Analytics | Uncovered customer purchase patterns and profitable combos using Python (EDA) and KNIME (MBA). |
| 3️⃣ | Visa Approval Classification Using Machine Learning | Predictive Modeling | Predicts visa approvals using ensemble ML models. |
| 4️⃣ | Inferential Analysis Marketing Insights | Statistics | Applied ANOVA, Chi-Square & Hypothesis Testing. |
| 5️⃣ | Automobile Customer Analytics | Data Cleaning | Analyzed car sales & customer patterns. |
| 6️⃣ | Hotel Booking Cancellation Prediction | Retail Analytics | Predict booking cancellation using Logistic Regression, KNN, Decision Tree. |
| 7️⃣ | Wine Sales Forecasting using ARIMA | Time Series | Forecasts next 12 months’ wine sales using ARIMA/SARIMA. |
| 8️⃣ | AllLife Bank Customer Segmentation | Unsupervised Learning | Clustered customers using K-Means & Hierarchical models. |
| 9️⃣ | ShowTime OTT Analysis | Regression | Linear regression to predict first-day OTT viewership. |
| Project | Description |
|---|---|
| Finance Risk Dashboard | Interactive dashboard visualizing company risk levels. |
| Wine Forecasting App | Streamlit app to predict monthly wine sales dynamically. |
| Visa Approval Predictor | Web app predicting visa certification probability. |
(Will be deployed using Streamlit Cloud & linked here.)
| Project | Description |
|---|---|
| Car Insurance Claims Analysis | Tableau dashboard analyzing car insurance claim patterns, customer demographics, and regional risk trends. |
| Retail Sales Performance (Power BI) | Power BI dashboard visualizing regional sales performance, profit margins, and category insights. |
(More visualization projects will be added soon — stay tuned!)
Mini Guides & Notes
Coming soon — I’ll share:
- Quick guides on EDA, Feature Engineering, Model Evaluation
- SQL tips & common interview queries
- Time Series forecasting notebooks
- “How I Structure Data Science Projects” tutorial
Mentoring Focus: Data Science | Analytics Career | Model Explainability | Business Storytelling
Languages: Python, SQL,
Libraries: Pandas, NumPy, Scikit-learn, Statsmodels, Matplotlib, Seaborn, XGBoost
Tools: Excel, Power BI, Streamlit, Tableau
Techniques: EDA, Predictive Modeling, Time Series Forecasting, Segmentation, Hypothesis Testing
Email: ray.nabankur@gmail.com
LinkedIn: linkedin.com/in/nabankur-ray-876582181
GitHub: github.com/nabankur14
"Data is not just numbers — it’s a story waiting to be told."
