As a Senior Data Scientist at Utopus Insights, I apply my passion and skills in solving challenging problems, finding useful information from hidden data, and deriving creative solutions for renewable energy. I have a Bachelor of Engineering in Computer Science from KCG College of Technology, where I developed a strong foundation in programming, machine learning, and data analysis.At Utopus, I lead the wind turbine component health monitoring project, using SCADA and vibration data to build failure prediction models for various components, such as bearings, gearboxes, shafts, and rotors. I also perform reliability management and asset underperformance analysis, using techniques such as power curve, yaw misalignment, ice detection, and blade angles. I have scaled the solution to over 25,000 wind turbines, including various platforms such as Vestas V90 3MW, 2MW, 3MW, and offshore. I have also contributed to other projects involving video highlights generation, damage detection, audio classification, and health bot, using audio signal processing, deep learning, TensorFlow, and pandas.