In this role, you will be responsible for model development, implementation & documentation.

You will be working with the independent model validation function of a large banking client and will involve end-to-end validation of risk and regulatory models across business functions, including first time validation, change based validation and annual validation of models. It will also involve development of challenger models as necessary. The role would also involve interaction with various stakeholder groups including model development, model owners/lines of business, auditors and client model validators.

We are looking for candidate with experience in risk, statistical model development and portfolio analytics. This would involve application of various industry best practices and techniques in the risk modeling area including but not limited to linear/ logistic regression, time series methods, Markov chain, survival modelling and advanced machine learning techniques.

The candidate would be primarily working for the analytics team of a large banking client and will be required to deliver intermediate to sophisticated level of data gathering, validation, data manipulation, model development and testing under mentorship of a project lead.

The responsibilities would span data gathering, analysis and preparation, development of component models, developer testing of the models, and preparing comprehensive model documentation in compliance with regulatory and internal requirements across different portfolios consumer/commercial, Credit-cards, Mortgage, etc.) for Risk and Financial Management

Responsibilities :

- End-to-end independent validation of credit risk and regulatory models - PD, LGD, EAD, Stress Testing, CECL, Credit Scorecards, AML and counter fraud models etc.

- First time (baseline), change based and annual validation

- Assess the models conceptually and quantitatively to ensure the model is suitable for the stated us

- Conduct necessary assessments to challenge the model effectively. Assess adequacy of model documentation

- Development of benchmark models using statistical/Machine Learning techniques

- Identify opportunities to enhance efficiency in model validation processes

- Assessment of the model monitoring and implementation process

- Prepare model validation report summarizing findings and provide recommendations

- Work across risk and regulatory modeling and data analytics projects

- Development, re-development and calibration of risk and regulatory models, including but not limited to credit decision scorecards, fraud and AML models, Basel IRB - PD, LGD, EAD, Stress Testing and IFRS 9/CECL models

- Model monitoring and implementation support

- Development of modeling strategies for automated decision making

- Develop and support the reports to be shared with senior management at the desired frequencies

- Excellent knowledge of various statistical techniques and proven skill in statistical modeling (Regression, Logistic Regression, Time series, Clustering, CHAID/Classification trees Etc.)

- Data and quantitative analysis to support modeling decisions

- Detailing model techniques and interpretation of variables used in the models be documented and presented to client Stakeholders

- Validation for the source data quality, forecast data quality as well as change management

- In addition to working on model development, the candidates would be required to present their analysis and model results to senior stakeholders in the client organization

Minimum qualifications :

- Master's degree or higher in Finance, Mathematics, Economics, Statistics, or equivalent experience

- Experience in BFS analytics, with experience in credit risk modeling/independent validation of models (Regression, Time Series, Competing Risk, Survival Models, Markov TPM, scorecards, etc.)

- Experience in retail and wholesale credit risk modeling

- Understanding of and experience in regulatory risk modeling/validation - SR 11-7, CECL, IFRS 9, CCAR, Basel IRB.

- Strong communication/presentation skills - written & verbal

- Self-driven, proactive, - can-do- attitude. Ability to work under ambiguity and with minimal supervision.

- Strong project management experience and demonstrated expertise in communicating and coordinating across multiple business units

- Expertise in SAS & Python/R

- Experience in managing projects independently

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