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ML Model Validation AVP

8.00 to 12.00 Years   Noida   25 Jul, 2019
Barclays Shared Services Pvt Ltd
Job LocationNoida
EducationNot Mentioned
SalaryNot Disclosed
IndustryBanking / Financial Services
Functional AreaSBU Head / CEO / Director
EmploymentTypeFull-time

Job Description

  • Provide independent review (IR) and challenge of different aspects of model (conceptual soundness, model performance etc.) across different model types (credit risk, fraud etc.) to a high degree of depth, as required by and detailed in the Bank s policies and standards. This role will be part of Group Risk IVU team.
  • Provide input to/support the governance and reporting processes related to model risk management.
  • Work on independent review of diversified set of models Fraud, IFRS9, CCAR, Basel, Decision, ECM, business strategy etc. for different products e.g. Credit Card, Home loan, Unsecured lending etc.
  • Perform technical analysis and/or build alternative benchmarks to new and existing models, in line with the requirements set out in the bank s standards and policies.
  • Review regulatory requirements to ensure compliance with different regulatory guidelines e.g. SR 11-7, PRA, FRB and Basel III.
  • Support the development and review conformance with appropriate policies including Group Model Risk policy.
What we re looking for:
  • Understanding of fraud or credit risk management practices and familiar with model usage, technology and governance.
  • Strong analytical skills with experience developing or validating predictive machine learning models (e.g. Random Forests, Gradient Boosted Machines and Deep Neural Networks etc.) on large data sets in Hadoop environments using tools such as Python, Spark and MLLib.
  • Advanced understanding of the quantitative techniques used in developing and validating models including Machine Learning, regression analysis, reject inference, decision trees and cluster analysis.
  • Proven expertise/in depth knowledge of one or more of the following areas of model risk management: Fraud, IFRS9, Basel, Application/Behavioural Risk scorecards, Existing Customer Management etc.
  • Hands-on experience in the use of statistical packages such as SAS, R, Python. Expert user of Microsoft Excel and other Microsoft Office tools.
  • An ability to identify and analyse appropriate external data sources for model development or validation
Skills that will help you in the role:
  • Relevant experience in a modeller/validator role in the financial services industry.
  • Certification in Machine Learning
  • Masters in Statistics, Mathematics, Economics, operational research, Engineering, MBA
,

Keyskills :
ecision treesmodel validationmicrosoft excelcredit riskrisk managementmachine learningmicrosoft officeneural networks

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