Quantitative Credit Risk Analytics, VP
Quantitative Credit Risk Analytics, VPFull Time PermanentLocation:
NY - 10020Job DescriptionQuantitative Credit Risk Analytics, VPHybrid Role - 3 days in office - 2 WFHSummaryThe VP-level quantitative credit risk analytics professional is responsible for developing methodologies and managing analytics for stress testing, risk appetite, CECL, economic capital and counterparty models including TM/PD, LGD, EL, and value-at-risk.
Candidate will join the Credit Risk Analytics group that partakes in model development over the full life-cycle of modes:
from methodology to design, to local implementation and validation.
Candidate will lead risk analytics initiatives and development of the assigned project.
Responsibilities Develop credit risk models, test, implement and document risk analytics.
Perform quantitative research to implement model changes, enhancements and remediation plans.
Work with stakeholders across business and functional teams during model development and implementation process.
Create tools and dashboards which can enhance and improve the risk analysis.
Conduct analysis on existing model short-comings and design remediation plans.
Maintain, update, and improve existing models.
Identify risks not captured by analytics, develop and implement methodology to quantify the materiality, and design a strategic plan to better integrate and manage such risk Support discussions with regulators as a subject matter expert Qualifications Master s Degree in quantitative subject; PhD is a big plus.
At least 5 - 7 years of experience in quantitative modeling for credit risk.
Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
Strong knowledge in statistics and statistical tools (hypothesis testing, regressions, time series models, MCMC Bayesian tool, state space model and etc.
) Deep understanding of main credit risk parameters (TM/PD, LGD, and EL) modeling.
Proficient programming skills in python (other languages such as R, SQL is a plus).
Experience in the use of machine learning techniques applied to risk modeling is a plus Strong project, management and organizational skills.
Strong writing and presentation skills.
Superior oral and written communication skills.
Ability to communicate effectively with managers that may not have quantitative backgrounds.
Recommended Skills Analytical Communication Computer Programming Coordinating Dashboard Data Analysis Apply to this job.
Think you're the perfect candidate? Apply on company site $('.
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on('click', function (event) window.
ExternalApply = window.
open('/interstitial?jobdid=j3v07y6q787jkgy2ft2', 'ExternalApply-j3v07y6q787jkgy2ft2'); ); Estimated Salary: $20 to $28 per hour based on qualifications.
NY - 10020Job DescriptionQuantitative Credit Risk Analytics, VPHybrid Role - 3 days in office - 2 WFHSummaryThe VP-level quantitative credit risk analytics professional is responsible for developing methodologies and managing analytics for stress testing, risk appetite, CECL, economic capital and counterparty models including TM/PD, LGD, EL, and value-at-risk.
Candidate will join the Credit Risk Analytics group that partakes in model development over the full life-cycle of modes:
from methodology to design, to local implementation and validation.
Candidate will lead risk analytics initiatives and development of the assigned project.
Responsibilities Develop credit risk models, test, implement and document risk analytics.
Perform quantitative research to implement model changes, enhancements and remediation plans.
Work with stakeholders across business and functional teams during model development and implementation process.
Create tools and dashboards which can enhance and improve the risk analysis.
Conduct analysis on existing model short-comings and design remediation plans.
Maintain, update, and improve existing models.
Identify risks not captured by analytics, develop and implement methodology to quantify the materiality, and design a strategic plan to better integrate and manage such risk Support discussions with regulators as a subject matter expert Qualifications Master s Degree in quantitative subject; PhD is a big plus.
At least 5 - 7 years of experience in quantitative modeling for credit risk.
Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
Strong knowledge in statistics and statistical tools (hypothesis testing, regressions, time series models, MCMC Bayesian tool, state space model and etc.
) Deep understanding of main credit risk parameters (TM/PD, LGD, and EL) modeling.
Proficient programming skills in python (other languages such as R, SQL is a plus).
Experience in the use of machine learning techniques applied to risk modeling is a plus Strong project, management and organizational skills.
Strong writing and presentation skills.
Superior oral and written communication skills.
Ability to communicate effectively with managers that may not have quantitative backgrounds.
Recommended Skills Analytical Communication Computer Programming Coordinating Dashboard Data Analysis Apply to this job.
Think you're the perfect candidate? Apply on company site $('.
external-apply-email-saved').
on('click', function (event) window.
ExternalApply = window.
open('/interstitial?jobdid=j3v07y6q787jkgy2ft2', 'ExternalApply-j3v07y6q787jkgy2ft2'); ); Estimated Salary: $20 to $28 per hour based on qualifications.
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