Data Solutions

I created a Power BI application that revolutionized insurance data collection and reporting processes by automating workflows and consolidating data from multiple environments (PROD, DEV, QA, and UAT). This solution ensured consistency and accuracy in analytics while significantly reducing submission processing time. Collaborating with underwriters, I optimized the Reconnect portal, improving data accuracy and user experience through enhanced functionality.

I developed and deployed machine learning models, including Logistic Regression, Clustering algorithms, and Decision Trees, to predict customer retention rates and analyze user behavior. These models boosted user engagement and supported business objectives by seamlessly integrating into analytics workflows. Using Python and BigQuery ML, I further improved model scalability and accuracy, enabling reliable predictions and data-driven strategies.

Building Scalable Dashboards with Google and Power BI

Automated Insurance Analytics

Machine Learning Initiatives

I designed and implemented a seamless data integration pipeline from Google Cloud Storage (GCS) to BigQuery using Apache Airflow. This pipeline enabled efficient querying and preprocessing, transforming raw data into valuable insights. By creating custom views in BigQuery and connecting them to Power BI, I developed interactive dashboards that analyzed user behavior patterns. These dashboards empowered stakeholders to make informed decisions and enhanced operational efficiency through real-time insights.