Risk Model Development - Analyst II

Citi; Gurugram District; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

Citi is seeking a qualified professional in Gurgaon to develop and validate stress loss models for CCAR/ DFAST/ CECL and climate risk. You will work with data preparation, segmentation, and econometric modeling to forecast secured portfolio losses.

Role involves building AI-driven workflows, rigorous testing, and documenting methodologies. Collaboration with governance, validation, and implementation teams is essential.

Qualifications

• Advanced degree required in Statistics, Applied Mathematics, Operations Research, Economics or Quantitative Finance.
• 2+ years of analytic experience in risk modeling or credit risk context.
• Experience with regression, time series, and econometric techniques.

Responsibilities

• Obtain and QC data for stress loss model development.
• Develop segment/account level stress loss models.
• Perform tests (sensitivity, back-testing) and validate/recalibrate models annually.
• Deliver comprehensive model documentation.

Skills

Python

SAS

Time series

Econometric modeling

Data analysis

Communication

Education

Master's degree (Statistics/Applied Math/OR/Quant Finance)

Tools

AI automation workflows

Regression analysis

Job description

The Position within Global Consumer Risk Management of Citi for CCAR/DFAST/CECL/Climate risk and other stress testing regulations for stress loss model development for the secured portfolios.

Core Responsibilities

• Obtain and conduct QA/QC on all data required for stress loss model development
• Develop segment and/or account level stress loss models
• Perform all required tests (e.g. sensitivity and back-testing)
• Validate/recalibrate all models annually to incorporate latest data. Redevelop as needed.
• Deliver comprehensive model documentation
• Work closely with cross functional teams, including country/region's business stakeholders, model validation and governance teams, and model implementation team
• Prepare responses/presentations for regulatory agencies on all regulatory models built

Education

Advanced Degree (Masters required/preferred) in Statistics, Applied Mathematics, Operations Research, Statistics, Economics, Quantitative Finance etc

Skillset

• Role involves strong programming (Python, SAS, AI automation using advanced workflows etc) and quantitative analytics (regression, time series, decision tree, linear/nonlinear optimization etc) skill.
• 2+ years analytic experience
• Experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and particularly econometric modeling of consumer credit risk stress losses
• Experience in model development or (risk/marketing)- credit scorecard development, Basel modeling, stress loss preferred or credit policy analytics
• Experience in end-to-end modeling process (data collection, data integrity QA/QC/reconcilements, pre-processing, segmentation, variable transformation, variable selection, econometric model estimation, sensitivity testing, back testing, out-of-time testing, model documentation, & model production implementation)
• Good communication skill to communicate technical information verbally and in writing to both technical and non-technical audiences
• Expected to work with moderate supervision and guidance
• Work as an individual contributor

Looking for a candidate with experience developing regression models for secured lending products combined with hands on experience designing AI-driven workflows to streamline and automate processes.

Job Family Group

Risk Management

Job Family

Model Development and Analytics

Time Type

Full time

Most Relevant Skills

Analytical Thinking, Credible Challenge, Data Analysis, Governance, Policy, Procedure, and Regulation, Risk Management Lifecycle.

Other Relevant Skills

Laws and Regulations, Management Reporting, Policy and Procedure, Referral and Escalation, Risk Controls and Monitors, Risk Identification and Assessment, Risk Remediation.

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