Arjun Nagal Email & Phone Number | Several years of experience in improving topline and bottomline metrics through data analytics applied to customer retention, upsell and fraud analytics in banking and insurance in the US, UK, Germany & India. Experience in financial risk management including asset-liability management, stress testing of the balance sheet and stochastic modelling of market risks Proficient in data analysis using machine learning techniques like gradient-boosting, random forests, linear and logistic regression, hypotheses testing, cluster analysis, with SAS & Python

Arjun Nagal

Several years of experience in improving topline and bottomline metrics through data analytics appli...
New York City Metropolitan Area, New York City Metropolitan Area, United States

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Arjun Nagal’s Email arjun_nagal@chubb.com

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Arjun Nagal’s Location New York City Metropolitan Area, New York City Metropolitan Area, United States

Arjun Nagal’s Current Industry Chubb

Arjun Nagal’s Prior Industry Scienaptic Systems | Abzooba | Icici Prudential | Wns Aviva | Citibank

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Work Experience

Chubb

SVP, Applied AI

2022-01-01 00:00:00 - Present

Scienaptic Systems

Engagement Leader

2016-04-01 00:00:00 - 2017-08-01 00:00:00

Abzooba

Director, Data sciences

2014-06-01 00:00:00 - 2016-04-01 00:00:00

Icici Prudential

VP: Business Intelligence

2007-11-01 00:00:00 - 2014-06-01 00:00:00

Wns Aviva

Manager Analytics

2006-01-01 00:00:00 - 2007-01-01 00:00:00

Citibank

Asst Mgr

2004-01-01 00:00:00 - 2006-01-01 00:00:00

Skills

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Languages

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FAQ About Arjun Nagal

Arjun Nagal is located at
New York City Metropolitan Area, New York City Metropolitan Area, United States

Arjun Nagal is a Several years of experience in improving topline and bottomline metrics through data analytics applied to customer retention, upsell and fraud analytics in banking and insurance in the US, UK, Germany & India. Experience in financial risk management including asset-liability management, stress testing of the balance sheet and stochastic modelling of market risks Proficient in data analysis using machine learning techniques like gradient-boosting, random forests, linear and logistic regression, hypotheses testing, cluster analysis, with SAS & Python