Turning Data into Insights, and Insights into Solutions.

I transitioned into data analytics from an engineering background, I knew I had a lot to learn. My early days as a Data Analyst and Technical Support Specialist were filled with challenges that pushed me to sharpen my problem-solving skills and think critically under pressure.

One of my most memorable experiences was when I worked with a fintech startup struggling with customer retention. They had a high churn rate, but no one could pinpoint why. My role was twofold: analyzing data trends to find patterns and assisting the support team in troubleshooting client issues.

I pulled customer interaction data using SQL and Python, identifying friction points where users frequently dropped off. At the same time, my technical support role gave me direct exposure to user complaints recurring system errors, slow transaction processing, and difficulties navigating the platform. By merging both perspectives data insights and real-time user feedback I uncovered a crucial insight: customers were abandoning transactions due to an overlooked UX flaw that delayed confirmation messages.

I worked closely with the product and engineering teams, showing them the data-backed evidence and real-world complaints from users. Together, we implemented a simple UI update and improved backend performance. Within three months, churn decreased by 30%, and user engagement grew significantly.

Work Terms

N/A