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The Model/Anlys/Valid Intmd Anlyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the subfunction/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.
Job Responsibility:
Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational
Supports the design, development, delivery and maintenance of best-in-class Risk programs, policies and practices for Risk Management
Reviews institutional or retail analytics and Models and other documents to ensure compliance with various regulatory and legal requirements
Identifies potential risks and escalates for further review
Handles preliminary investigations, assists with reconciliation procedures and prepares routine correspondence
Creates and maintains reports for control, tracking, and analysis purposes and ensures appropriate and secure retention of documents
Works with more senior staff in investigating and responding to customer and operational complaints
Interacts and works with other areas within Risk Management, as necessary
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets
Participate in building champion/benchmark models for CCAR, CECL, IFRS9, and other regulatory/internal purposes for Citi's international and U.S. secured portfolios
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
Create 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
Requirements:
5+ years experience
Proficient in Microsoft Office with an emphasis on MS Excel
Consistently demonstrates clear and concise written and verbal communication skills
Self-motivated and detail oriented
Demonstrated project management and organizational skills and capability to handle multiple projects at one time
Bachelor’s/University degree or equivalent experience
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
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
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