Perform Root Cause Analysis explaining model performance to second line of defense and Policy teams for Business risk decisioning.
Analyze & bring out Insights for Credit Risk Non-Regulatory Scoring/ Non-Scoring Segmentation models adding business value.
Present model performance to senior stakeholders, CROs, Risk Policy managers, Sponsors explaining the heath of the model.
Partnering with Risk Policy leads to help understanding the levers / cut off adjustments required in scores baked in Risk strategies to bring in incremental benefit / loss mitigation to business.
Explain model performance to second line (Model Risk Management) of defense providing rational for model performance deterioration.
Respond to queries from 3rd Line of Defense (Internal and External Auditors) on model performance.
Work effectively across cross functional teams
Development, Implementation, Policy, Validation and Governance teams
coordinating the horizontal model usage and maintenance activities.
Perform analysis for benchmark models and other adhoc analysis as required by business/validation teams.
Develop knowledge and drive discussions on Model usage across channels, score range with Risk Strategy managers.
Conduct QA/QC on all steps (e.g., input data, model output, etc.) required for model monitoring and production forecast reporting.
Deliver comprehensive write-up of ongoing model performance assessment, Annual Model Review / Revalidation documents.
Understand model variables and economic forecasts and conduct drill down analysis and reporting of model performances.
Deliver end user computing process related mandates.
Expected to manage own projects independently.
Train and mentor junior team members on Model Monitoring, generating insights from different analysis required by business.
Requirements
Advanced Degree (Bachelors required or Masters preferred) in Statistics, Computer Science, Operations Research, Economics, etc.
Strong programming (SAS, R, Python, etc.) skills.
Experience in reporting tools
Excel, Tableau.
Understanding of traditional modeling processes (linear/ logistic regression, segmentation, decision tree) and machine learning algorithms (Random Forest, Gradient Boosting, XG Boost, SVM, etc.), time series, linear/nonlinear optimization.
Understanding of relevant model metrics / KPIs & bring out insights on model performance tracking.
Good communication skill to communicate technical information verbally and in writing to both technical and non-technical audiences is a must.
Extensive experience in model monitoring/validation, performance scorecards, etc. in Excel, Tableau, Cognos, etc.
Experience in developing optimal/ automated solution of reporting processes using SAS, Excel VBA, Tableau will be a plus.
2+ Years reporting & analytics experience.
Extensive experience in reporting (risk/marketing) in portfolio reporting, model monitoring, generating business insights.
Experience in adoption of AI in bringing efficiency into core functional process, automating reports would be a plus.
Tech Stack
Cognos
Python
Tableau
VBA
Benefits
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.