Summary
Linkesh Diwan is a Senior Engineer with 13 years of international experience across the US, EU, and Asia, specializing in renewable energy engineering, risk assessment, and technical due diligence for M&A. At Hartford Steam Boiler he leads technical D&D for renewable projects across EURO and AMER markets and provides engineering support to Munich Re’s global financing and acquisitions teams. His background spans hands-on solar system design, product development for manufacturing, and creating guidelines used by underwriters and claims teams, blending field experience with standards development. Trained in energy engineering and mechanical engineering (KTH, Universidade de Lisboa, Amrita) and certified in predictive analytics, he combines quantitative analysis with practical asset-inspection insights. He has a proven track record of improving manufacturing and installation processes, coordinating international supply chains, and shaping national/international standards. Colleagues value him for bridging technical nuance and commercial decision-making across cultures and markets.
13 years of coding experience
4 years of employment as a software developer
Master of Science (MSc), Mechanical Engineering, Environomical Pathways for Sustainable Energy Systems, A, Master of Science (MSc), Mechanical Engineering, Environomical Pathways for Sustainable Energy Systems, A at KTH Royal Institute of Technology
Certificate Crash Course, Entrepreneurship/Entrepreneurial Studies, Certificate Crash Course, Entrepreneurship/Entrepreneurial Studies at ESADE Business School
Bachelors of Technology, Mechanical Engineering, First Class with Distinction, 8th Rank, Bachelors of Technology, Mechanical Engineering, First Class with Distinction, 8th Rank at Amrita Vishwa Vidyapeetham
Master’s Degree, Energy Engineering and Management, 18 of 20, Master’s Degree, Energy Engineering and Management, 18 of 20 at Universidade de Lisboa
Certified Specialist in Predictive Analytics, Data Science, Certified Specialist in Predictive Analytics, Data Science at The CAS Institute
English, Malayalam, Hindi, Swedish, Japanese