Data Analyst | Aspiring Data Scientist & AI Engineer
Passionate about turning data into insights and building intelligent systems through analytics, machine learning, and open-source collaboration.
Real-world data analysis projects demonstrating analytical thinking and technical depth.
Exploratory Data Analysis
Performed end-to-end exploratory data analysis on the Google Play Store apps dataset to understand market demand, category competition, monetization patterns, and factors influencing app quality. The project involved extensive data cleaning, statistical exploration, and visualization to uncover high-growth app categories and strategic insights for potential app developers.
Exploratory Data Analysis & Interactive Dashboard
Performed exploratory data analysis on 981 smartphone models to understand pricing patterns, market segmentation, and specification trade-offs. Analyzed relationships between RAM, storage, processor speed, and pricing to identify key drivers of smartphone pricing. Insights were presented through clear visualizations and an interactive Streamlit dashboard.
Exploratory Data Analysis
Performed exploratory data analysis on global layoff datasets to analyze industry trends, company layoffs, geographic distribution, and macroeconomic impacts. Built visualizations to understand layoffs by year, sector, and company size to uncover meaningful patterns in the global tech employment landscape.
Core performance attributes — analyst edition.
From the tunnel to the pitch — a progression of growth and execution.
Started programming with Java and C and learned core programming fundamentals — algorithms, logic, and structured thinking.
Began working with Python for data analysis and machine learning. Built real-world exploratory data analysis projects on Google Play Store, Smartphone Market, and Global Layoffs datasets.
Started contributing to open-source projects and documentation improvements in the PySAL ecosystem, preparing for Google Summer of Code and deeper research opportunities.
Milestones that reflect both technical progress and personal character.
Represented school in the district level football tournament, demonstrating discipline, teamwork, and performance under pressure.
Actively contributing to the PySAL ecosystem, improving documentation quality and notebook accessibility
in libpysal and esda.
Built complete, end-to-end data analysis pipelines for real-world datasets from raw data cleaning to actionable insights and dashboards.
I'm a data enthusiast passionate about extracting meaningful insights from data and building intelligent analytical systems.
My journey combines strong analytical thinking with the discipline and teamwork developed through competitive football. Alongside academic learning, I actively build real-world projects and contribute to open-source ecosystems, including the PySAL library to deepen my understanding of data science and machine learning.
I believe the best insights come from disciplined exploration: cleaning messy data, asking the right questions, and communicating findings with clarity. Exploring the world of AI.
Open to collaborations, open-source contributions, and opportunities in data analytics and machine learning.