Arpit Narain

Global Head Of Financial Solutions - Artificial Intelligence & Quant Modeling at Mathworks

Arpit Narain, CFA, FRM, CQF has extensive experience in the financial industry, specializing in quantitative risk modeling and analytics. Arpit Narain,'smost recent role was as the Global Head of Financial Solutions - Artificial Intelligence & Quant Modeling at MathWorks, where they oversaw the expansion of the business across various sectors including climate risk, financial risk, and investment management. Prior to that, they were a Director at KPMG US, where they led quantitative risk modeling engagements and implemented projects related to traded risk platforms and market risk capital. Arpit also established the Quantitative Risk Modeling & Derivatives Valuations group at KPMG, providing advisory services to financial services clients globally. Arpit Narain, has previous experience at The Smart Cube, Torux Private Limited, and HSBC, where they worked on various quantitative trading and risk modeling projects. Arpit's expertise lies in model validation, stress testing, portfolio analytics, and risk management. Arpit Narain, holds multiple certifications, including CFA, FRM, and CQF.

Arpit Narain has a Bachelor of Engineering degree in Electronics & Telecommunication Engineering from the Army Institute of Technology (University of Pune), obtained between 2003 and 2007. Arpit also holds a Financial Risk Manager (FRM) certification from the Global Association of Risk Professionals (GARP, USA), completed in 2009. Additionally, they are a Chartered Financial Analyst (CFA) Charterholder from the CFA Institute, USA, achieved in 2012. Arpit has a Certification in Quantitative Finance (CQF) from Fitch in London, specializing in Quantitative Trading & Risk Management. Arpit Narain, also completed the Advanced Risk & Portfolio Management Program (ARPM) in the USA in 2017, focusing on Quantitative Investment and Risk Management.

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New York, United States

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Mathworks

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Mathworks is a producer of MATLAB, a program for data and statistical analysis.


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1,001-5,000

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