Irosha Wickramasinghe
About Irosha Wickramasinghe
Irosha Wickramasinghe is the Head of Credit Risk Analytics at MassMutual in New York with extensive experience in risk management and model development across various financial institutions.
Head Of Credit Risk Analytics at MassMutual
Irosha Wickramasinghe is currently the Head Of Credit Risk Analytics at MassMutual in New York, New York. In this role, they have developed advanced machine learning algorithms specifically designed for credit risk assessment. They utilize a comprehensive understanding of both the theoretical and practical aspects of risk management to lead the development and implementation of sophisticated risk models. Their work directly contributes to enhancing the company's overall risk management strategies.
Past Role at New York Life Insurance Company
From 2019 to 2021, Irosha Wickramasinghe served as Corporate Vice President at New York Life Insurance Company in New York, New York. During their two years in this role, they gained significant experience in managing corporate risk and developed extensive expertise in model validation and review, specifically focusing on market risk measures and credit risk-factor models.
Experience with Zenik Capital LLC
Irosha Wickramasinghe worked at Zenik Capital LLC, a Proprietary Hedge Fund, from 2017 to 2019. In this capacity, they worked in the Greater New York City Area, honing their skills in advanced risk management strategies and credit value adjustment. This role helped deepen their understanding of investment risk and risk management.
Education and Academic Background
Irosha Wickramasinghe holds an impressive academic background with a BSc from the University of Colombo, a PhD from Northeastern University (2000-2005), and a Post Graduate degree from the Massachusetts Institute of Technology (2006-2007). Their education provided a strong foundation in risk assessment and modeling, which they have effectively applied across their various professional roles.
Technical Skills and Expertise
Wickramasinghe is proficient in multiple programming languages, including Python, C++, VBA, and SQL. Their technical skills facilitate the development and implementation of complex risk models. Specialized in credit value adjustment and value at risk calculations, they have a robust background in creating models that enhance counterparty exposure measurement and overall risk management strategies.