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Soham Sarkar

Data Aspirant

[email protected]

Resume

Hello, I am

Soham Sarkar.

1

Python Project

About Me

Hi, I’m Soham Sarkar, a data science enthusiast currently pursuing my M.Sc. in Statistics at IIT Kanpur.

I’m developing my skills in data analysis, visualization, and statistical modeling, with a strong interest in applying them to real-world problems. My current toolkit includes Python, SQL, Excel, and Power BI, which I use to explore datasets, uncover insights, and communicate findings effectively.

I'm passionate about continuous learning and excited to take on freelance projects and internships in data science, analytics, and business intelligence.

Key Skills

Python

Excel

Machine Learning

SQL

Power BI

My Projects

Awards & Certificate

Python: Beginner to Advanced For Data Professionals

SQL for Data Science

Math and Statistics For AI, Data Science

Let's Connect

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

[email protected]

https://www.linkedin.com/in/sohamsarkar09/

https://github.com/sarkarsoham1

Python Project

EDA and Hypothesis Testing for Credit Card Launch

Domain/Function: Banking

• Analyzed customer data to identify target segments for a new credit card • Performed hypothesis testing using Z-test to evaluate card performance • Tools: Python (Pandas, Seaborn, Matplotlib, Numpy), Statsmodels

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Engagement

View Project
on GitHUB

EDA and Hypothesis Testing for Credit Card Launch

Visualized income, credit limit, and credit score trends across age groups to uncover patterns in customer financial behavior.

EDA and Hypothesis Testing for Credit Card Launch

Test group shows a wider spread and higher transaction amounts than control, indicating potential impact of the new banking strategy.

Project Details

In this project, I analyzed a fictional bank’s dataset to extract actionable insights about customer behavior and branch performance. The goal was to assist the bank’s leadership in making data-driven decisions to improve profitability and customer satisfaction.

Key Highlights:
- Performed exploratory data analysis (EDA) to uncover patterns in customer demographics, account activity, and service usage.
- Identified high-value customer segments and analyzed their contribution to revenue.
- Visualized key metrics such as customer distribution, product usage trends, and branch-level performance using Python (Pandas, Seaborn, Matplotlib).
- Recommended strategies to enhance customer retention and optimize resource allocation.

This project demonstrates my ability to clean and analyze real-world business data, draw meaningful insights, and present findings clearly and concisely.