Risk Model Development- Intermediate Analyst

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Job Overview

Citi’s Risk Modeling Solutions department is responsible for the development, delivery, and monitoring of all credit risk models across Citi’s consumer lending portfolios globally.  These models span two core activities; granting and managing credit to individual customers and delivering loss forecasts for stress testing (ex. CCAR), loan loss reserving (ex. CECL), and business planning.   This position sits within the Global Mortgage Regulatory Model Development team and specifically part of the Global Climate and Global Benchmarking Models team and is responsible for developing benchmark risk models for Citi's U.S. secured portfolios for CCAR, CECL, climate risk, and other regulatory/internal usage. 

Responsibilities:

Position responsibilities include but not limited to the following activities:

• Participate in building champion/benchmark models for CCAR, CECL and other regulatory/internal purposes for Citi's U.S. secured portfolios.
• Independently perform data cleansing and analysis, identify static and dynamic portfolio drivers and macroeconomic drivers for portfolio risk performances, build PD/EAD/LGD models and conducting statistical analysis and backtests, perform forecast sensitivity analysis and model robustness tests, and provide model implementation and validation support with minimal manager support.
• Create and review Model Development Document for validation and supporting Annual Model Reviews and Ongoing Performance Assessment of implemented models.
• Participate in model revalidation, model change and related documentation and validation support efforts.
• Ensure timely completion of assigned projects with high quality.
• Work closely with cross functional teams, including country/region’s business stakeholders, model validation and governance teams, and model implementation team
• Prepare responses/presentations to regulatory agencies on all CCAR/CECL/IFRS9/Climate models built
• Effectively communicate model results to both technical and non-technical senior audience.
• Present model results with over-sight  for approvals
• Good understanding of regulatory requirements
• Good communication skill to communicate technical information verbally and in writing to both technical and non-technical audiences

Qualifications:

• 5+ years of experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, or econometric modeling and in-depth knowledge on the use of statistical models to solve business problems (years of experience in Master or PhD programs of Statistics, Economics, Finance, Biomedical Engineering or other highly quantitative discipline counts).
• Experience of end-to-end credit risk modeling highly preferred.
• Experience of CCAR and CECL preferred.
• Strong programming (SAS, SQL, Python, R, etc.) and quantitative analytics (regression, time series, decision tree, linear/nonlinear optimization etc.) skills preferred.
• Strong communication skills required to translate model design, specification and performance details to technical and non-technical audiences.

Skillset:

• Quantitative Analysis
• Statistical Modeling
• Loss forecasting/Loan Loss Reserve Modeling/Econometric Modeling
• Credit Risk Modeling
• CCAR/CECL Regulations
• SAS, SQL, Python, R

Education:

• Master’s/University degree or equivalent experience in Economics, Mathematics, Statistics, Finance of other quantitative discipline
• PhD degree in Statistics, Economics, Finance, Biomedical Engineering or other quantitative discipline preferred.

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Job Family Group:

Risk Management

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Job Family:

Model Development and Analytics

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Time Type:

Full time

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Most Relevant Skills

Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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