Balaka Dutta

Client Assignment: Siemens Healthineers (AIRAD Data Science Team) • Develop scalable data science and machine learning solutions to support research and innovation in healthcare applications • Collaborate with cross-functional teams of researchers, engineers, and domain specialists to translate complex R&D problems into practical AI solutions • Contribute to model validation, performance optimization, and deployment within production-oriented environments

•Developed and integrated custom MCP server tools to extend AI assistant and LLM capabilities for business workflows and automation Designed LLM-driven solutions enabling real-time reasoning, reporting, and decision support across diverse use cases •Accelerated NVH simulations with a fast AI optimizer, enabling rapid evaluation with 90% accuracy •Designed DL pipelines for nodal displacement and structural analysis with 92% accuracy •Presented advanced AI solutions to clients, showcasing real-world problems

Python Devloper for BMW Group • Deployed updated software to the system with E-Sys and perform a test cycle for network provisioning • Automated functional test cases with python scripts and control code version with Git • Maintained efficient communication between relevant stakeholders to ensure the proper closure of defects • Execute end-to-end test life cycle using test data management tool (Octane and Jira) along with DLT traces

Project Management in AI RAD Companion Integrated various reporting mechanisms from different business streams by creating and maintaining interactive visualizations in Power BI and Azure DevOps. Collaborated with project managers identifying critical metrics and KPIs, through data interpretation analysis, and delivering actionable insights to leadership using BI dashboards. Automated yearly forecasting and actual budget tracking model with Microsoft Excel macro and Visual Basic for Applications.

Developed AI solutions for detecting shipping container IDs from an image/video stream, delivering a robust pipeline and deploying with AWS SageMaker, by achieving an accuracy of 99% for vertical IDs. Skills: Image processing, Annotation, Object detection, Amazon s3(AWS), YOLO, Mobile V-Net, OpenCV, TensorFlow, Trello

Quality Assurance • Collaborated with managers and business partners in an agile development environment for the quality assurance of 5 web-based financial applications • Analyzed, prepared, created, and planned test cases, strategy, and bug discovery, along with database management using Excel and SQL

Computational Engineering - Technical Application Field (Digital Signal Processing )

Bachelor Thesis: Automated Irrigation with Sun Tracking Solar Cell and Moisture Sensor also Sensor Based Automated Shading of Green House