Quantitative Risk Analyst

The Counterparty Risk Analytics (CRA) team is responsible for developing and maintaining the methodologies to calculate counterparty credit risk exposures of OTC derivatives, exchanged-traded derivatives, security financing transactions, and margined loans. The models are used for advanced Basel regulatory capital calculations, CCAR/Internal Capital Adequacy Assessment Process (ICAAP) estimations, and internal risk management measures (PFE/EPE). Additionally, the team provides live-deal analysis to business and risk management by calculating credit exposure factors at trade and portfolio levels, estimating allowable collateral levels, and determining initial margin requirements. The team also conducts impact analysis for capital optimization initiatives and new regulatory rules related to counterparty risk and ensures models and data logic is implemented correctly in credit risk systems.

Develops, enhances, and validates the methods of measuring and analyzing data quality of historic market data which is used for calibration of counterparty credit risk simulation models. This includes defining market data sources, collecting data, validating data, and developing data cleansing and enhancing logic based on quantitative methods. The work will mainly consist of historical time-series collection, analysis, develop and enhance the methodology for data spike/staleness/outlier detection, validity checking, and data cleaning with data issues remediation. Once potential data exceptions are detected, validate if they are true data quality issues through alternative sources (other data providers, or internal trading business risk managers, etc). Based on findings, take appropriate actions for these “exceptions”. Conducts statistical analysis for risk related projects and data modeling/validation. Prepares statistical and non-statistical data exploration, validate data, identify data quality issues. Conducts data analysis, data mining, read and create formal statistical documentation, reports and work with Technology to address issues. Analyzes and interprets data reports, make recommendations addressing business needs. Uses Predictive modeling methods, optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary. Automates data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations. Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. What we will need from you: Up to 3 years of experience in statistical data analysis or quantitative risk analysis in financial service industry, in case of no full-time position experience at least internship in one of considered areas is required Experience in Market Risk, Counterparty Credit Risk, Derivatives Pricing or Time Series Analysis is preferred At least basic knowledge about properties and pricing of traded financial instruments and their derivatives Proficient in Microsoft Office with an emphasis on MS Excel Statistical analysis and programing experience (SQL and Python are preferred) 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 Master or higher degree preferred, with an excellent academic record in a quantitative field (e.g. mathematics, statistics, econometrics, computer science, physics, etc.).