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Mission: Enable data-driven energy optimization using ML and IoT Manage ML use cases life cycle Turn each ML use case into a reusable ML library included in the offercreation services Collaborate with other execution teams and provide necessary inputs and support Key responsibilities: Analyze historical and real-time IoT data for performance insights Collaborate with Energy Efficiency Consultant to share / review findings related to energy optimization opportunities Assess data quality, perform feasibility studies (Remote / Onsite), and validate possibility of ML model based optimization for identified optimization opportunities Use low-code/no-code Analytics platforms to build and deploy models Manage ML-based use cases from definition to deployment Support continuous improvement of ML models by incorporating the changes in the site conditions through continuous monitoring model performance Prepare and Present insights and recommendations to internal and external stakeholders Support the filed trials (Implementation) for testing the ML recommendations / current set points, filed trial data analysis along with Energy Efficiency consultant Provide necessary inputs for execution planning, ensure timely completion of project tasks, communicate any roadblocks to Project Manager and adjust the delivery schedule Report the issues, track progress and test the fixes related to ML model development to deployment in analytics platform Support the creation of ML library/template to be included in the offer Collaborate with other execution teams, provide timely support and inputs Handle ML portion of the projects Independently with minimum support Profile / skills 20+ years of experience in energy performance or digital transformation in industrial environments Strong understanding of working principles, operations and control aspect of utility systems, including chilled water, compressed air, cooling towers, pumping systems, fans systems, Hot water System, Steam systems, AHU .