Vidyasagara Reddy Thodime

I worked on Palantir Foundry to develop and optimize data pipelines for processing critical flight-related data generated by onsite engineers at various airports. These data points, captured before each flight's takeoff, were ingested and processed using PySpark within the Palantir Foundry environment.

Additionally, I developed the integration with the service request analytics application, which processes and loads logged tickets into Palantir Foundry for further analysis. I also built a dynamic dashboard using Palantir Slate to enhance decision-making and operational efficiency. This dashboard enabled back-end engineers to quickly access historical ticket data, view previous solutions, and respond faster to ongoing issues.

This streamlined process significantly reduced response times and improved issue resolution, saving the company €5 million annually by optimizing resource allocation and minimizing delays.

I worked as a data engineer and developed and managed data pipelines in PySpark within Palantir Foundry to streamline patient appointment scheduling and optimize Operation Theater slot utilization for the NHS. I was responsible for processing and analyzing large datasets to identify patterns in appointment cancellations and resource availability. By designing efficient data workflows, I improved operational efficiency, reduced patient waiting times, and enhanced the overall healthcare experience. Collaborating with cross-functional teams, I ensured that data was accessible, accurate, and actionable for informed decision-making.

I developed a financial crime monitoring and AML solution using Azure and its suite of technologies. The system detects, monitors, and reports suspicious financial activities in real-time.

The solution integrates machine learning models for anomaly detection and uses Azure Data Lake to store large financial datasets scalablely. Azure Service Bus enables seamless, reliable communication between different system components, ensuring data flows smoothly across the solution. Azure Functions are also used for serverless computation, triggering automated responses to specific events, such as suspicious transactions. Meanwhile, Azure Logic Apps automate and orchestrate the process of generating and submitting compliance reports, reducing manual effort.

By combining these technologies, the solution enabled rapid detection of financial crimes, enhanced the accuracy of AML monitoring, and ensured compliance with regulatory requirements, all while reducing operational overhead and improving response times.