AVP- Non-Retail Credit Validation

Location

Bangalore | India

Job description

Quantitative Analysis

• Use programming skills for working hands on model validation data analysis, perform statistical tests.
• Use statistical knowledge to interpret and advise on the statistical tests results.

Stakeholder interaction

• Work across multiple teams (Model Development, Credit, Credit Risk) to understand data issues, modelling and business-related issues for performing good model validation.
• Work closely with GBS and remote HO validation team.
• Write final validation reports as per regulatory expectations.

Governance Functions

• Keep the Model inventory updated.
• Onboard new models, Action items and their timelines.
• De-commission retired models.
• Send follow up reminders on existing Action items.

Mentorship

• Beside working hands-on on validation projects, should also have the necessary aptitude to mentor junior team members, review their work and ensure high quality final delivery.

Senior Management Support

• Support the senior management in HO to prepare presentations and response for committee meeting, Audit etc.

Job Context:

Specific Accountabilities

• Understand all key statistical tests used for modelling viz. model stability, accuracy and risk discrimination and their consequent impact on Bank s risk profile.
• Should challenge model development teams on techniques, model design, variables logic etc.
• Keep close watch on Audit and regulatory expectations and incorporate them during validation assessment.
• Maintain timelines and expected quality for final deliverables.

• Bachelors / Master s degree in quantitative science (statistics, mathematics, economics) from a reputed institution.

Minimum Experience

• 8+ years of experience in successfully executing Model Validation and Monitoring role for a bank of similar product landscape and complexity.
• Should have hands-on validation experience on Corporate Ratings Models and Regulatory models (IFRS9 - PD, EAD and LGD)
• Should have understanding of traditional and new modelling techniques: linear and logistic regression, timeseries, Decision Tree etc. Random Forest, XGboost, Neural Networks, etc), Pluto tasche method.
• Should have experience and strong knowledge of SAS, Python and R. Should be willing to learn newer technologies which are open source based and should be comfortable in working in collaborative manner on a cloud based environment.
• Excellent interpersonal communication skills - verbal and written, and have experience of working with stakeholder.

Job tags

Salary