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Statistics student with a strong interest in data analysis and data driven decision making. Experienced in end-to-end data science projects using Python, R, and SQL.
Featured proof
1 callfor an EDA profile
Open case study →Proof of work
Each project explains the problem, method, findings, and limitations—not just a list of technologies.
A Python package for fast, structured exploratory data analysis on pandas DataFrames. One function call produces a data overview, column profiling, missing value detection, duplicates, outliers, correlations, and data quality warnings. Built to remove repetitive boilerplate from the EDA process.
1 callfor an EDA profile
A case study on a subscription business using the KKBox dataset. The focus is not just predicting churn, but understanding why it happens. The findings are turned into practical retention strategies.
6 monthsdata period
Customer segmentation on the Online Retail II dataset using an RFM approach. Five clustering algorithms were compared objectively through internal validation, not chosen manually. The final result splits customers into two main segments.
5,878customers analyzed
Capabilities
Proficiency: Advanced
Experience: 3 years
Processing, analyzing, and automating data workflows with the Python ecosystem.
Proficiency: Advanced
Experience: 2 years
Presenting data patterns and findings through clear, relevant visuals.
Proficiency: Advanced
Experience: 2 years
Using statistical methods to test assumptions and produce evidence-based conclusions.
Proficiency: Intermediate
Experience: 2 years
Producing reproducible statistical analyses and visualizations with R.
Proficiency: Novice
Experience: 1 year
Retrieving, cleaning, and summarizing relational data through SQL queries.
Proficiency: Intermediate
Experience: 2 years
Translating analytical results into insights that are easy to understand and act on.
Open source
Explore implementations, code structure, and technical experiments directly from the source.
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