Risk Model Monitoring Execution Analyst-c09

Generate production forecasts for economic scenarios. Produce additional on-demand runs to support analytical requests from peer groups and model sponsors.
- Implement new or enhanced model monitoring report in production environment
- Continuously work to maintain and improve governance controls relates to implementation and production process
- Generate standard reporting, comparison with previous results as well as drill down analytics for productions forecasts.
- Conduct QA/QC on all steps (e.g., macro-economy series, model output, etc.) required for production process.
- Deliver comprehensive write-up of production results and process as per internal and regulatory standards
- Understand model variables and economic forecasts and conduct drill down analysis and reporting of model production forecasts.
- Perform analysis for benchmark models and other ad hoc analysis as required by business/validation teams
- Work closely with cross functional teams, including country/region’s business stakeholders and model analytics
- Maintain and improve automation solutions for production process
- Ensure timely completion of governance controls and production results under tight timelines
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Responsibilities**: Qualifications**: Education**:

- Develop and implement automated solutions for model monitoring and transformation using tools such as SAS, Excel, Python, Visualization Tool like Tableau
- Collaborate with cross-functional teams (analytics) to understand model monitoring requirements and reengineer SAS code
- Design and maintain Data Quality check to ensure accuracy, efficiency, and reliability of model monitoring data.
- Conduct data analysis to identify trends, patterns, and opportunities for optimization.
- Generate insights and actionable recommendations based on analytical findings to support strategic decision-making.
- Create visually compelling dashboards and presentations to communicate key insights to stakeholders.
- Continuously monitor and improve existing model monitoring processes to enhance efficiency and effectiveness.
- Ensure timely completion of governance controls and deal tight timelines
- Master's degree in a quantitative field such as Mathematics, Statistics, Computer Science, or related field.
- Proven experience in report automation, data transformation, and analytics.
- Proficiency in programming languages and tools such as SAS, Python, Excel, Power BI, or similar.
- Strong analytical skills with the ability to interpret complex data sets and draw meaningful conclusions.
- Excellent communication and presentation skills with the ability to convey technical concepts to non-technical stakeholders.
- Detail-oriented with a focus on accuracy and quality of work.
- Ability to work independently and collaboratively in a fast-paced environment.
- Master's degree in a relevant field

This position will focus on the model performance tracking, production and model implementation of CCAR/DFAST/ICAAP and CECL stress loss models for Citi's product portfolios on an US & international basis, including but not limited to leading the following activities:
**Roles and Responsibility**:

- Obtain/implement model from model development to production environment, and obtain updated data from countries/regions and/or Risk Architecture to run primary & benchmark CCAR models. Document all production related activities around production/model implementation/performance tracking.
- Run quarterly model prediction performance back-testing and sensitivity analysis against accuracy and other required model performance triggers for production models
- When performance shifts are observed, perform diagnostic analytics around drivers on the models
- Document & review base and stress CCAR model performance with assigned countries & regions quarterly and assist countries and regions in their use of the CCAR/DFAST models in business activities such as loss forecasting/benchmarking their loss forecasts and assessing the risk of various lending segments (i.e., Risk Appetite)
- Review model performance and drivers of any gaps or deterioration in model performance with MRM, IRMO, and regional and country risk managers
- Perform full, formal annual model review to follow MRM’s guidance and standards.

**Qualifications**
- Degree in Statistics, Applied Mathematics, Operations Research, Statistics, Economics, or other highly technical quantitative discipline
- 0 to 2 years’ experience in developing or tracking quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and econometric modeling of consumer credit risk
- Strong working knowledge in SAS Programming, ability to code from scratch, automate SAS processes etc.
- Strong working knowledge in UNIX environment, working on FTP sessions (Putty/Tectia etc.)
- Expertise in successfully executing either the model development or model performance tracking components of an analytical, econometric modeling-driven stress loss process
- Experti