Model Validation 2nd LOD Sr. Analyst

The Risk Analytics, Modeling and Validation role involves the development, enhancement, and validation of methods for measuring and analyzing all types of risks, including market, credit, and operational. In areas related to credit risk, individuals in this role develop, enhance, and validate models for measuring obligor credit risk, or early warning tools that monitor the credit risk of corporate or consumer customers, besides being involved in Loss Given Default studies. They also develop and maintain key risk parameters like default and rating migration data, usage given default data and transition matrices. This role is vital to the company as it provides a scientific and systematic approach to assessing and mitigating risks, thereby ensuring the company's financial stability, protecting its assets, and supporting its overall business strategy. The responsibilities of a Model Validator include performing model validations, annual model reviews, ongoing monitoring reviews (on Low and Medium Model Risk Rating (MRR) models) and model limitation remediation reviews for one or more model / product types under the supervision of a Validation Lead (VL). The role also involves providing effective challenge to the model development process, evaluating testing approach and results for individual models, assessing ongoing performance monitoring of the models, contributing to regulatory and internal audit related responses, collaborating with other teams within Risk and the Business, assisting with preparing reports and meeting materials, and supporting the process of designing, developing, delivering, and maintaining best-in-class qualitative model validation process standards. The ideal candidate for this role should have 5-8 years of experience in Quantitative Finance, Risk management, Analytics, Model Development or Model Validation. They should possess excellent partnership and teamwork skills, ability to formulate findings clearly and concisely in written form, good verbal communication skills, good analytic and creative thinking abilities, adept at analysis and documentation of results, ability to multi-task and work well under pressure, and deliver results under tight deadlines. Proficiency in programming languages like Python, MATLAB, C/C++/C#, VBA or other coding languages is required, along with knowledge of financial markets and products. Qualitative or quantitative model risk management experience is a plus, along with strong technical skills in time series analysis, statistics, and econometrics. Education requirement for this role is a Master's degree. Key skills required include Analytical Thinking, Business Acumen, Credible Challenge, Data Analysis, Governance, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, and Statistics. If you are a person with a disability and need a reasonable accommodation to use the search tools and/or apply for a career opportunity, please review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster for more information.,