Associate Consultant on Machine Learning for Client: Chevron USA

Job Role: Machine Learning-Based Predictive Maintenance System for Oil Equipment:

Remotely led the development of a machine learning model for Chevron’s oil equipment monitoring from the offshore delivery center in India. Collaborated virtually with on-site engineers to understand the data collected from IoT sensors on approximately 1,000 pieces of rotating equipment. Developed and fine-tuned a random forest algorithm using Python and scikit-learn to predict potential equipment failures based on historical sensor data. The model analyzed parameters such as vibration patterns, temperature fluctuations, and pressure readings to identify early signs of malfunction.