Hello, I am Arpan Surin

I am a Data Scientist from India.

transforming messy, unstructured datasets into clear narratives that drive business decisions.

With a technical foundation in Computer Science and AI/ML from SRM Institute of Science & Technology, I bring an advanced algorithmic lens to traditional data analytics. I don’t just report numbers; I uncover the "why" behind the trends to help organizations navigate complex business challenges with precision.

View Resume | LinkedIn | GitHub | Gmail

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Technical & Professional Skills


MySQL, PostgreSQL

SQL

Data Pipeline

Data Pipeline

Python

Python

GitHub

GitHub

Excel

Excel

Docker

Docker

PowerBI

PowerBI

Machine Learning

Machine Learning

Featured Projects


End-to-End Customer Churn and CLV Prediction System

Python | PostgreSQL | Pandas | Scikit-learn | FastAPI | Streamlit | Power BI

An end-to-end e-commerce data pipeline built in Python. This project covers raw data ingestion, data cleaning, feature engineering, machine learning for churn and CLV, a REST API backend, a Streamlit frontend and an LLM-powered customer insights experience.

Project summary

GitHub - ArpanSurin/Drivers-earning-performance-and-risk-analysis

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Driver Earnings & Performance Analytics

PostgreSQL | Power BI

An interactive dashboard designed to understand DAX functions and driver revenue distribution across different cities, earning segments (active vs at risk) and also the driver count.

Project summary

GitHub - ArpanSurin/Drivers-earning-performance-and-risk-analysis

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Hotel Revenue Analysis

Power BI | SQL Server

This project analyzes historical hotel booking data to understand revenue performance across years and compare City Hotels vs Resort Hotels. The analysis was performed using SQL Server, and insights were visualized through an interactive Power BI dashboard.

Project Summary

GitHub - ArpanSurin/Hotel-Revenue-Analysis: This is a basic power bi project created to understand dashboard creation & derive revenue insights

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Experience


EduSkills Internship

Altair: Data Science | Virtual

July 2025 - September 2025



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