Jagjit Kaur

Associate Software Engineer at Accenture Pvt Ltd (2024-09 – Present)

Developing digital twin and 3D simulation solutions using NVIDIA Omniverse with Python backend and React.js frontend integration.

Designed and implemented end-to-end simulation logic using Python, controlling traffic flow, pedestrian behaviour, and flood-based road blocking in NVIDIA Omniverse improving simulation accuracy by 30%.
Developed Python scripts to process incoming data and update USD stages, reducing manual intervention by 40% and improving real-time scenario transitions.
Automated simulation execution using Python and API-based workflows, ensuring efficient and scalable real-time rendering.
Enabled real-time interaction between Omniverse and a React.js application via REST APIs and MQTT connection for live control and visualization.
Created 15+ custom 3D models in Isaac Sim based on client specifications, applying realistic physics, lighting, and collision parameters to achieve 95% simulation accuracy.
Automated simulation workflows using Python scripting and USD models, reducing manual setup time by 40% and enhancing overall project efficiency.
Improved system performance by 25% through modular React components and event-driven architecture for real-time visualization.
Developed an interactive simulation dashboard integrating a Python backend with a React.js frontend, enabling real-time 3D control and visualization.
Collaborated with NVIDIA Omniverse experts to implement USD-based digital twins for robotics visualization, ensuring seamless asset management and scene rendering.

Data Analyst (Intern) at Nine A Business Connect Pvt Ltd (2024-01 – 2024-06)

Developed data analytics solutions and business intelligence dashboards for toll traffic and revenue analysis.

Toll Traffic & Revenue Dashboard: Engineered and maintained SQL databases and data warehouses, processing million records/month with 99% system uptime and data visualization, reducing manual reporting time by 60%.
Power BI Dashboard Development: Developed an interactive dashboard using SQL and Python for ETL processes.
Revenue Anomaly Detection: Integrated Python scripts and Power BI to identify 25% peak-hour usage surges and revenue anomalies, enabling 30% faster decision-making.

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