Sep 2022 – Present · 3 yrs 6 mos

• Build predictive models using various machine learning tools to predict the possibility of equipment failure.
• Develop algorithms using Reinforcement learning and Deep learning models for predictive maintenance.
• Design algorithms to track and detect anomalies in multiple sensors data.
• Designed, developed and analysed the underlying Machine learning model based Architecture.
• Implemented big data processing pipelines to compute features, labels and KPIs for the model on Azure big data technologies including feature engineering, model training, data cleaning, processing and validation.
• Detailed data analysis, testing and performance visualisation creation to improve model's precision, recall, AUC and other KPIs at every iteration.
• Documented data testing scenarios and set up exception monitoring pipelines on a regular cadence .
• Collaborated across teams to reuse computed data for trending feeds and search relevance improvement.