Citibank India

Job Description

This Position is within Global Consumer Risk Management of Citi for CCAR/CECL/Decision Scores model development for the Unsecured portfolios. (e.g., credit cards, installment loans, ready credit etc.)
The responsibility includes but not limited to the following activities:

Obtain and conduct QA/QC on all data required for CCAR/CECL/Decision Scores model development
Develop segment and/or account level CCAR/CECL/Decision Scores models. Developing Underwriting, Line management, Account management, Collection and Recovery models.
Executing the above models in compliance with GCCFRP and in accordance with the Model Development Procedures within Risk
Validate/recalibrate all models annually to incorporate latest data. Redevelop as needed.
Perform all required tests (e.g. sensitivity and back-testing). Deliver comprehensive model documentation and perform implementation tests
Work closely with cross functional teams, including business stakeholders, model validation and governance teams, and model implementation team
Work closely with policy managers in establishing the swap set analysis and PnL optimization using the models.
Create story boards, presentations and project plans for discussions with senior management
Support the regulatory submissions for Citi on CCAR/CECL and work on adhoc requests from Business and Independent Risk
Prepare responses/presentations to regulatory agencies on all CCAR models built
Train and mentor junior modeler in developing innovative models in compliance with policies and procedures

Qualifications:
Advanced Degree (Masters required, PhD preferred) in Statistics, Applied Mathematics, Operations Research, Economics, MBA (Finance), or other highly quantitative discipline
2 years experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and particularly econometric modeling of consumer credit risk stress losses
Experience with dynamics of unsecured products a strong plus
Expected to work with moderate supervision and guidance
Ability to work effectively in cross functional teams, including country/regions business stakeholders, model validation and governance teams, and model implementation team
Exposure to various stress loss modeling approaches at the segment or account level preferred
Able to communicate technical information verbally and in writing to both technical and non-technical audiences

Technical Skills:

Strong technical skills in modeling procedures is required (regression, time series, decision tree, linear/nonlinear optimization etc.)
Strong in SAS/SQL/Oracle/Unix/Microsoft Word, Excel and PowerPoint
Basic programming skills in Python or R is required
Strong communication skills to present technical information verbally and in writing to both technical and non-technical audiences is required.
On-the-job Python coding experience is preferred.
Machine Learning knowledge is preferred
Big Data concepts understanding is preferred
Education: MBA/ PGDMr r r r r r r Any Graduate
Industry: Banking