Data Analyst | Business Analyst

Power BI | SQL | Python | Excel | Tableau

I turn data into insights that help businesses make better decisions.

I work across data analysis, business intelligence, and visualization to uncover patterns, answer business questions, and turn complex data into clear, actionable insights.

“Before asking what the data says, I ask what the business needs to know.”

Download Resume

View My Projects

Featured Projects

Customer Behaviour Analysis

Analyzed customer purchasing behavior to identify key patterns and customer segments, using Python and EDA to uncover insights that support customer retention, targeted marketing, and business growth.

Tools: Python · Pandas · NumPy · Matplotlib · Seaborn

View Project →

Stock Market Portfolio & Risk Analytics

Analyzed stock market performance to build conservative and aggressive investment portfolios, using Python and Power BI to evaluate risk, returns, and investment opportunities.

Tools: Python · Pandas · Matplotlib · Power BI · Excel

View Project →

Predicting Employee Retention Using Machine Learning

Analyzed employee data to identify factors influencing attrition and retention, using Python and machine learning to predict employee turnover and support data-driven HR decisions.

Tools: Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn

View Project →

Coffee Shop Sales Analysis

Analyzed stock market performance to build conservative and aggressive investment portfolios, using Python and Power BI to evaluate risk, returns, and investment opportunities.

Tools: Power BI · DAX · Excel

View Project →

View My Full Portfolio

CustomerIQ — AI-Powered Customer Intelligence & Retention Analytics

Python · SQL · Machine Learning · Power BI · FastAPI · Generative AI

Project Overview

Built an end-to-end customer intelligence platform that combines predictive analytics, customer segmentation, financial risk analysis, and generative AI to help businesses identify churn risk and prioritize retention actions.

The Business Problem

Customer churn is not only a retention problem — it is a revenue and profitability problem.

CustomerIQ transforms customer transaction and engagement data into actionable intelligence by identifying customers at risk, quantifying revenue and profit exposure, and helping teams determine who to contact first and why.

Key Questions

Which customers are most likely to churn?
How much revenue and profit are at risk?
Which customers should we prioritize for retention?
Which customer segments and RFM groups are most at risk?
What retention actions should the business prioritize?

Approach

Raw Data → Data Cleaning → SQL Analytics → Churn Modeling → Customer Scoring → SQLite → Power BI + AI Query Engine

Explore the dashboard and ask CustomerIQ questions to see how analytics can turn customer data into retention decisions.

CustomerIQ AI Assistant

Ask questions. Get data-backed customer insights.

Interact with CustomerIQ using natural language to identify high-risk customers, explore churn patterns, quantify financial exposure, and prioritize retention actions.

Interactive Dashboard

Explore customer risk and retention insights.

Explore the interactive Power BI report to analyze customer segments, churn risk, customer value, revenue exposure, profit exposure, and retention priorities.

Try CustomerIQ AI →

Explore Interactive Dashboard →

View GitHub Repository →

Full Walkthrough →

“We don't just analyze data. We understand the questions businesses ask—and use data to find the answers that matter.”

About Me

I’m a Data Analyst who likes to start with the question, not the dashboard.

My journey into analytics began in risk management and fraud prevention, where I learned to spot patterns, investigate anomalies, and understand the story behind the numbers. Today, I use SQL, Python, Excel, Power BI, and Tableau to turn complex data into clear insights and practical business decisions.

I’m driven by curiosity, problem-solving, and the challenge of finding the insight that can make a real difference.