Statistician & Data Analyst. With a strong interest in statistical modeling and causal analysis.
I help organizations make sense of "noisy" data. By combining traditional frequentist statistics with modern Bayesian machine learning, I build robust systems for quantitative research.
Toolkit & Focus
Technical proficiency
Programming & Tools
Python (Pandas, Matplotlib), Microsoft Excel, SQL, and Tableau.
Core Competency
Primary Expertise
Applying propensity matching and IV analysis to observational datasets.
Snapshot
Current Read
Emotional Intelligence — Daniel Goleman
Location
Sylhet, BD
Project Portfolio
A selection of my quantitative analysis work, ranging from academic papers to interactive dashboards.
Customer Churn Analysis
Excel / Data Analysis / Business Insights
A comprehensive cleaning and analysis of ~50,000 customer records to identify early churn signals and improve retention strategies.
This project analyzes customer churn for a subscription-based business using exploratory data analysis.
The objective was to identify early churn signals and provide
actionable recommendations to improve customer retention.
Dataset: ~50,000 customer records
Main finding: Early-tenure customers account for the majority of churn
Business value: Enables targeted onboarding and retention strategies
Business Context
Customer churn is a critical challenge for subscription-based businesses, as acquiring new customers
is significantly more expensive than retaining existing ones.
This analysis simulates a real-world business scenario where understanding
why customers leave is essential for sustainable growth.
Business Questions
Which customer segments exhibit the highest churn rates?
How does customer tenure impact churn probability?
Are early-stage customers more likely to churn?
Which behavioral factors are most associated with churn?
Key Insights
Customers with 1–12 months tenure accounted for approximately 58% of total churn,
indicating high risk during early onboarding.
Customers with tenure greater than 24 months showed churn rates below 15%,
suggesting strong long-term stability.
Over 60% of churn occurred before customers fully adopted core services.
Key takeaway: Early customer experience is the most critical determinant of churn.
Visual Evidence
Churn rate by support interactions
Churn rate by tenure
Business Recommendations
Strengthen onboarding programs during the first 12 months
Track early engagement metrics to flag at-risk customers
Deploy targeted retention campaigns for new users
Tools Used
Microsoft Excel
GitHub
HTML & CSS
The Library
Reviews, learning points, and activities beyond the code.
Selected Reading
Emotional Intelligence
Daniel Goleman
"An essential read that argues IQ isn't the sole predictor of success. Goleman explores how self-awareness, empathy, and social skills are often more critical for leadership and personal fulfillment."
Key Learning
The 'Amygdala Hijack': Learning how our emotional brain can override our rational brain and how to manage those impulses through mindfulness.
