I didn't start in data — I started with people.
My background in Sociology trained me to look for patterns in human behavior, read between the lines of social dynamics, and ask why before jumping to what. That same instinct translates directly into how I approach data: I don't just clean datasets and build dashboards, I try to understand the people behind the numbers.
After completing the RevoU Full Stack Data Analytics program, I found that my social science lens actually sharpens my analysis, especially when the data is about customers, employees, or passengers. Understanding why people behave the way they do isn't a soft skill, it's an analytical edge.
Right now I'm looking for opportunities where data meets people, whether that's in data analytics, HR analytics, or anywhere organizations want to make smarter decisions.
Data querying, joins, aggregations, and database management
Data analysis, cleaning, and visualization with pandas & matplotlib
Interactive dashboards and data storytelling
Advanced formulas, pivot tables, and data modeling in Excel & Google Sheets
Cloud-based Python notebooks for collaborative data analysis
Cross-functional collaboration, coordination, and communication
Completed intensive training covering end-to-end data analysis processes, including data cleaning, exploration, analysis, and visualization. Utilized SQL, Python, Tableau, and spreadsheets to translate complex datasets into actionable recommendations.
End-to-end data analysis on 129,000+ airline passenger records across 24 variables. Performed data cleaning, missing value treatment, outlier assessment, and exploratory analysis to identify key factors driving passenger dissatisfaction. Built an interactive Tableau dashboard for stakeholder reporting and developed data-driven recommendations for service improvement prioritization.
Prepared and cleaned credit card and user datasets for RevoBank Indonesia to support customer segmentation analysis. Performed data type validation, categorical value standardization, missing value treatment, duplicate removal, and business rule filtering including expired card exclusion and credit limit validation across 5,500+ card records and 2,000 user profiles.
Designed and developed interactive data visualizations for a personal expense tracker with realistic merchant data. Created clear and insightful charts to track spending patterns, identify trends, and support personal financial decision-making through effective visual storytelling.
Conducted comprehensive e-commerce data analysis on TokoBli marketplace data. Performed data cleaning, exploration, and sales performance evaluation to uncover business insights. Delivered actionable recommendations through structured presentation and team lead simulation exercises.
Applied SQL querying techniques to extract, filter, and analyze data from relational databases. Demonstrated proficiency in writing complex queries including JOINs, aggregations, subqueries, and window functions to derive meaningful business insights from structured datasets.
I'm currently looking for opportunities in data analytics. Whether you have a question or just want to say hi, feel free to reach out!