**Geospatial Data Analyst | Geographer | Data Execution and Operations | Logistics | Communication

I'm an ambitious and growth-oriented professional eager to apply knowledge, develop expertise, and contribute to organizational success. Known for a strong work ethic, adaptability, and the ability to learn quickly in fast-paced environments.

Geospatial & Analytics

GIS Remote Sensing Spatial Analysis WebGIS Data Visualization

Technical

Python Pandas NumPy scikit--learn Matplotlib Seaborn Leaflet Power BI KNIME Excel Git GitHub

Business & Administrative Support

Reporting Documentation Presentations Data Management

Communication

Professional Communication Team Coordination

West Bengal 2026 Election — Results & Swing Analytics Geospatial analysis of the 2026 West Bengal Assembly Election — party performance, winning margins, and constituency-level 2021→2026 vote-swing mapping using choropleths. Python GeoPandas/Folium Pandas Choropleth Mapping Key Focus: Turns raw, tabular election results into spatial insight by joining results to constituency boundaries and visualizing shifts between two elections. View Project

Meghalaya Smart Tourism Platform (STIS) Interactive WebGIS Smart Tourist Information System for Meghalaya — routing, offbeat-site scoring, nearby-facility discovery, and a tourism dashboard. JavaScript Leaflet.js WebGIS Geospatial Key Focus: Applies GIS/geospatial scoring logic to real-world tourism planning, built for my MSc dissertation on Meghalaya's geotourism potential. View Project Live Demo

Telecom Customer Churn Analysis & Prediction End-to-end Data Analytics + Machine Learning + Business Intelligence project on the IBM/Kaggle Telco Churn dataset — built with KNIME (cleaning, feature engineering, modelling) and Power BI (executive dashboard), verified in Python. KNIME Power BI Python Logistic Regression / Decision Tree / Random Forest Key Focus: Rebuilds and audits an earlier churn workflow, then turns the corrected model into a business-facing dashboard with KPIs and retention recommendations. View Project

Retail Customer Segmentation (K-Means) Segments 200 retail customers via K-Means clustering on income and spending score, with cluster profiles translated into marketing recommendations. Python scikit-learn Unsupervised Learning Key Focus: Converts an unsupervised ML output into plain-language customer segments a marketing team could actually act on. View Project

Uber Fare Prediction — Polynomial Regression Engineers Haversine distance and time-based features from 200k Uber rides, then fits polynomial regression to predict fare amount. Python scikit-learn Geospatial Feature Engineering View Project

Titanic Survival Prediction Binary classification on the Kaggle Titanic dataset comparing Logistic Regression, Decision Tree, and Random Forest models. Python scikit-learn Classification View Project

Advanced Power BI Advanced GIS & Remote Sensing Business Intelligence KNIME Workflows Applied Python for DS

Transforming geospatial and data-driven insights into practical business solutions. Interested in GIS, data analysis, visualization, operations, logistics, and business processes, with a strong focus on problem-solving, communication, coordination, and continuous learning.