On my Product Analytics Dashboard project, I collected, cleaned, and transformed more than 100,000 user activity records using Python and SQL. I used exploratory data analysis to examine engagement, retention, and platform performance.
I developed interactive Power BI dashboards to track DAU, MAU, conversion rate, and user retention, and automated reporting workflows to support business decision-making.
For CareerIQ, I developed an AI-powered career recommendation platform using Python, SQL, Pandas, Scikit-learn, and Streamlit. I implemented machine learning models for role prediction and skill-gap analysis, and created personalized recommendations based on users' skills, education, and experience.
