In this role, you will be responsible for model development, implementation & documentation - for a BFS client in the US

Responsibilities

• Work hands-on in development, re-development, and calibration of risk and regulatory models for banking book including deposit runoff, average balance forecasting, prepayment models for assets portfolio

• Data and quantitative analysis to support modelling decisions and ensure the correctness of the market data sourced from several vendors.

• Work on the development of model methodologies, algorithms, and diagnostic tools for testing model robustness, sensitivity, and stability.

• Detailing of model techniques and interpretation of variables used in the models to be documented and presented to client stakeholders.

• Develop model performance metrics and a detailed model monitoring plan to ensure continued use of these behavioural models

• Development of benchmark models may be required

• Help develop thorough technical documents for distribution and presentation to senior management, model developers, auditors, and regulators.

• Bringing in industry best practices and consultative inputs to help deliver continuous value to client engagements in advanced risk analytics.

Qualifications we seek in you!

• Educational qualification: master\'s and bachelor\'s degrees in quantitative disciplines, like, mathematics, statistics, economics, computer science and engineering, etc.; MBAs must have bachelor\xe2\x80\x99s degree in above-mentioned disciplines

• Relevant experience:

• Hands-on experience in SAS is needed. It is good to have Python coding experience.

• Experience in developing, validating models and risk management of credit risk models.

• Knowledge of various statistical techniques and proven skill in regulatory and non-regulatory credit risk modelling

• Understanding and experience of the regulatory risk model development/validation guidelines \xe2\x80\x93 SR 11-7, Basel IRB, CCAR, CECL, IFRS9 etc.

• End-to-end development or independent validation of credit risk and regulatory models including but not limited to \xe2\x80\x93 PD, LGD, EAD, Stress Testing, CECL, Credit Scorecards, AML and counter fraud models etc.

• Develop statistical/mathematical and machine learning based models, rule fine tuning/optimization, testing, reviewing, and performing validation activities and prepare end to end model documentation.

• Detailed knowledge of data analysis / analytics / mining techniques

• Hands on expertise in SQL, ETL, SAS, Python, R working with large data sets.

• Excellent knowledge of various statistical techniques

• Strong client management and communication/presentation skills \xe2\x80\x93 written & verbal.

• Self-driven, proactive, \xe2\x80\x9ccan-do\xe2\x80\x9d attitude. Ability to work under ambiguity and with minimal supervision.

• Strong networking, negotiation and influencing skills.

• Knowledge of credit risk management for retail and wholesale lending products

• Hands on experience in Machine Learning modeling techniques