Balance Sheet Management Modeling – Sr. Analyst AVP

The Balance Sheet Management Sr. Analyst is a seasoned professional role. The Sr. Analyst is expected to apply in-depth disciplinary knowledge, contributing to the development of new methodologies (statistical models and tools), data processing, visualization and analysis tools and approaches, and the improvement of processes and workflows for the Balance Sheet Management function.

The Balance Sheet Management modeling group is the critical team within the treasury group and is responsible for developing statistical and non-statistical methodologies. This team plays an important role in overall balance sheet management and has direct impact on the Citigroup's Capital. The work in this space is subject to heightened regulatory focus and scrutiny.

This team is responsible for the development of the Deposit duration, Fund Transfer Pricing, Customer Pricing and other models and tools that are used in the IRRBB and treasury space. The models and tools are built using the standard sophisticated well known modeling techniques used across industry which helps in better Interest rate risk management for the firm.

The Sr. Analyst will be responsible for end-to-end development of statistical models covering such asset classes as Deposits or Fixed Income Securities, or specific function such as Asset Allocation strategy. As part of those responsibilities, the Sr. Analyst would be expected to demonstrate analytical/statistical skills in the design, implementation, governance of models, strong communication skills in documenting and presenting their work, stakeholder management and interaction skills allowing the analyst to clearly and efficient understand requirements and develop a model or approach to meet those requirements. For non-statistical modeling projects / tasks, the Sr. Analyst would be required to integrates subject matter and industry expertise within a defined area. Demonstrate good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Regularly assume informal leadership roles within teams.

Responsibilities:

• End-to-end development and governance and support of models in treasury/IRRBB space.
• End-to-End model development includes econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes. This includes the calculation of Net Interest Income ("NII"), Non-Interest Revenue ("NIR"), Interest Rate Exposure ("IRE"), Economic Value Sensitivity ("EVS"), and other associated interest rate risk metrics.
• Applies analytical thinking and knowledge of statistics / modeling / data analysis tools and methodologies. Gives attention to detail when making judgments and analytical recommendations based on the analysis of information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results.
• Model governance and support includes reviewing and timely submission of model documentations such as - Model development document (MDDs), Annual Model Review (AMRs), Ongoing Performance Assessment (OPAs), Model Change Addendum (MCAs), Limitation Record Change (LRCs) to Model Risk Management and other stakeholders.
• Develop and maintain a comprehensive modeling system that maintains consistent approach to data quality and modeling methods, audit, back test, tracking, annual validation which is critical in reducing the model operating risk.
• Must be able to present technical matters in a way that is meaningful to the audience and align with Model Risk Management on modeling and validation practices and have periodic check-ins with them.
• Ability to build key relationships with finance and business teams' ability to influence people and empower team members to be proactive and focused on partnerships and results.
• Create a culture of accountability and strict quality control of the data integrity and modeling processes

Qualifications:

• 6-8 years of relevant statistical modeling /econometrics experience in financial domain
• PG / Masters / PhD in quantitative discipline such as Statistics, Economics, Mathematics, or related discipline is preferred. Certifications such as FRM, CFA is a plus.
• Experience in developing econometric models and deep understanding of statistical techniques such as Linear Regression, Logistic Regression, Time Series, Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration and Machine Learning Techniques, etc.
• Working experience with Artificial Intelligence/Machine Learning techniques and packages (ChatGPT, Copilot) etc.
• Hands-on experience in programming and modeling using Python and related packages (GitHub, DataFlame) is must. Working knowledge of statistical packages like SAS/R is a plus.
• Experience with SQL and databases. Experience in excel VBA is plus.
• Domain knowledge and experience in PPNR, Fixed Income Securities, Mortgage Modeling, Deposit Modeling, Asset Liability Management, Interest Rate Risk, Capital Planning, etc. Broad understanding of financial products, accounting principles, investment, accrual products and corporate finance concepts
• Excellent presentation skills, ability to translate complex financial schedules into meaningful presentations is critical; demonstrated analytical skills including the ability to synthesize quantitative and qualitative data to draw conclusions and assist on decision making
• Ability to build key cross functional and cross business relationships.
• Assume informal leadership roles within team and team management skills and ability to managing multiple projects and deadlines.

Education:

Bachelor's degree in Finance and Business or related fields

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