Company: Capgemini India
Role: Senior AI ML Analyst
Project: Equinor Statoil Global Operations
About Project:
This project involved designing, implementing, and developing AI/ML-driven data processing and predictive analytics solutions for global enterprise operations at Canon and Equinor Statoil. The work focused on intelligent automation systems targeting predictive maintenance, document digitization, OCR automation, and scalable ML deployment to optimize operational efficiency, reduce manual processes, and enable data-driven decision-making
Key Technical Works:
- Developed machine learning and time-series forecasting models for predictive maintenance and operational analytics.
- Built OCR and CNN-based deep learning solutions for intelligent document extraction and automation.
- Processed and transformed large ERP and CRM datasets for ML model training and analytics workflows.
- Assisted in deploying ML models using Docker and Kubernetes in scalable production environments.
- Monitored system and model performance using Dynatrace and Datadog tools.
- Collaborated with cross-functional teams to improve automation, operational efficiency, and enterprise data processing systems.
- Contributed to the AI-driven predictive maintenance project by developing forecasting pipelines and analytics models to optimize equipment lifecycle management and reduce operational downtime.
- Worked on the intelligent document automation project by implementing OCR and deep learning-based extraction systems for processing invoices, operational reports, and enterprise business documents.
- Supported the enterprise MLOps deployment project by containerizing ML applications using Docker and assisting Kubernetes-based deployments with monitoring through Dynatrace and Datadog for scalable production environments.
Skill Sets:
Python, Scikit-learn, Pandas, CNN, OCR, Time-Series Forecasting, Docker, Kubernetes, Dynatrace, Datadog, ERP/CRM Data Processing, Machine Learning, Deep Learning, and Predictive Analytics.