Poonam Damani, Ceem
About Poonam Damani, Ceem
Poonam Damani is a Senior Catastrophe Modelling Analyst at AXIS Capital, specializing in catastrophe modeling for the Asia Pacific region. She has a strong statistical background and has previously worked at Aon and AXIS Capital, enhancing her expertise in the field.
Work at Axis Capital
Poonam Damani currently holds the position of Senior Catastrophe Modelling Analyst at AXIS Capital, where she has been employed since 2021. Prior to this role, she worked as a Catastrophe Modeling Analyst at the same company from 2017 to 2020. During her tenure at AXIS Capital, she has focused on catastrophe modeling, particularly for the Asia Pacific region. Her experience in this role has contributed to her expertise in the field.
Previous Employment Experience
Before joining AXIS Capital, Poonam Damani worked as a Senior Analyst in Analytics Catastrophe Modeling at Aon from 2020 to 2021. Her earlier roles include a Development Team Intern at Certis CISCO Singapore in 2015 and a Financial Advisor Intern at Great Eastern Financial Advisers Private Limited from 2015 to 2016. Additionally, she interned at Wilmar International in 2013. These positions have provided her with a diverse background in analytics and financial services.
Education and Expertise
Poonam Damani earned a Bachelor of Business Administration (B.B.A.) with a focus on Actuarial Science from Nanyang Technological University, completing her studies from 2013 to 2016. She also attended Raffles Junior College, where she completed her A Levels, and Raffles Institution, where she obtained an Associate of Arts degree. Her educational background has equipped her with a strong statistical foundation, enhancing her analytical capabilities in catastrophe modeling.
Catastrophe Modeling Skills
Poonam Damani specializes in catastrophe modeling, particularly within the Asia Pacific region. She is proficient in utilizing various catastrophe models, including RMS, AIR, RQE, and IF. Her skills in these areas are supported by her strong statistical background, which contributes to her effectiveness in analyzing and interpreting data related to catastrophe risks.