Resume

Leading development of enterprise data products, AI protocols, and cloud infrastructure across 7 business units and 15 countries.

• ▶ Led development of Zeiss Master Data product across 7 Business Units and 15 countries, streamlining data availability and consistency
• ▶ Generated €850,000 in revenue by building an ETL pipeline using Databricks with Unity Catalog, acquiring over 30 customers
• ▶ Saved 60% in data retrieval and integration time by developing the Model Context Protocol (AI-MCP) to standardize AI–data interactions across 15+ products
• ▶ Reduced access management time by 60% by deploying Azure Entra ID authentication across 15+ products
• ▶ Developed business dashboard for Zeiss Global Customer Center showcasing 30+ metrics to global stakeholders and the Zeiss CFO
• ▶ Engineered a reduction of 30+ hours per week by developing 10+ Azure Function Apps, acquiring 115 business customers
• ▶ Reduced resource deployment time by over 40% for 20+ data products using Terraform scripts
• ▶ Led the creation of eVA 3.0 data platform with mesh architecture using Data Products as nodes

Performed root cause analysis, automated reporting, and optimized distributed database systems for client-facing analytics.

• ▶ Generated $10M in revenue by performing RCA on client claims analytics data, identifying risk and saving 2% of cost
• ▶ Reduced latency by 1.2% for dynamic data loading over a distributed database by fragmenting data across nodes
• ▶ Reduced monthly error rate by up to 80% by implementing VBA-based automation in report generation using Excel Macros
• ▶ Awarded client appreciation award for reducing anomaly reporting time by 91.6% by automating data retrieval, processing, and reporting

Built data processing pipelines and machine learning models for energy demand prediction and optical character recognition.

• ▶ Improved energy demand prediction by 22% by building a data processing pipeline and modeling on 90+ dimensions using PCA
• ▶ Generated interactive visualization graphs for dashboards comparing real-time data and past forecasts using Seaborn and Matplotlib
• ▶ Achieved 96.73% accuracy on handwriting recognition for digital cataloging of manual energy readings using OpenCV and Keras
• ▶ Implemented an RNN-based model using TensorFlow trained on handwriting data samples with and without text separation

Research focus on computer vision, generative adversarial networks, and deep learning for image processing and video analysis.

• ▶ Achieved 93.26% accuracy in deepfake video detection using a multimodal approach combining teeth detection and lip–audio synchronization
• ▶ Achieved a Jaccard coefficient of 91.44 and Dice score of 93.27 in unsupervised image registration using a deep model based on VoxelMorph
• ▶ Generated 200+ fingerprints with a 97.83% no-artefact detection rate using StyleGAN and its style transfer property

GPA 8.52 | Top 1% of Graduates. Built a Java application for automated exam question paper generation integrated with a SQL database.

• ▶ Graduated in the top 1% of the batch with a GPA of 8.52
• ▶ Reduced time for exam question paper generation by 40% by building a Java application integrated with a SQL database over the network