About Quantitative Risk and Stress Testing
The Quantitative Risk and Stress Testing (QRS) group’s mandate is to develop, maintain, and enhance credit, market, and counterparty risk analytics to consistently measure risk, optimize capital, dimension risk appetite, and allocate these metrics to businesses and geographies; and to support Basel, internal and external stress testing, and loan loss reserve processes. Additionally, the group reviews and approves credit risk rating processes and analyses rating performance across Citi’s portfolios. QRS comprises more than 250 quantitative risk analysts and other professionals located in nine cities and six countries, and is responsible for over 200 risk models used within Citi.
Responsibilities:
- Develop, maintain, and enhance models for credit risk, market risk, and/or counterparty credit, including risk capital and/or stress testing
- Develop and implement methodologies, algorithms and diagnostic tools for testing model robustness, stability, reliability, performance, and quality control of modelling data
- Develop, maintain, and enhance technical documentation, including project plans, model descriptions, mathematical derivations, data analyses, process and quality controls
- Support various tasks in response to regulatory and internal risk management requirements
Qualifications
- Graduate degree in Economics, Finance, or another quantitative field (Mathematics, Physics, Computer Science, etc.) is required. Master or higher degrees are advantageous, as is exceptional academic record (rewards, recognition, etc.)
- Demonstrable interest in applying sophisticated mathematical/analytical techniques to solve real-world problems—especially in banking, finance, or risk management—is required
- Experience of one or more of the following topics is advantageous but not essential: derivative pricing, risk management practices, numerical methods including Monte Carlo simulation, statistical hypothesis testing, banking- or trading-book products, credit risk modelling, market risk modelling, counterparty risk modelling, risk capital modelling, stress testing
- Fluent English
Skills
- Solid programming skills, with experience of statistical/data analysis techniques and numerical implementations and some familiarity of modern software development tools, is required. Specific experience in SAS, Python, R, C/C++, UNIX, databases, and version control systems is particularly advantageous
- Ability to develop exceptional writing skills (in English), with pre-existing ability to synthesise complex technical information and explain it clearly, is required
- Strong written and verbal communication skills, with ability to synthesise complex technical information and explain it clearly, is required
- For more senior applicants, actual industry experience in developing and maintaining detailed technical documentation for models, model validation, projects plans and processes, is advantageous
Personal traits
- Highly motivated, with ability to work both independently and collaboratively
- Logical and thoughtful approach to work, with ability to perform well under pressure to meet tight deadlines
- Giving careful attention to detail, with capability to deliver high quality results
- Potential to build trusted relationships confidently at all levels
What’s on offer?
The successful candidate will have the opportunity to work on a wide range of cutting-edge analytical problems, relevant for senior management decision making (CRO, CFO, Board) and regulatory management. He or she will interact with highly-experienced quantitative analyst and risk management professionals across multiple risk stripes and geographies, and in so doing gain an expansive view of the firm and its business lines. This is an opportunity to grow within a high-quality team quantitative analysts in a challenging area of the financial industry working for one of the world’s leading companies.
QRS Openings
QRS has openings for Officers and Assistant Vice Presidents (depending on experience) in the following departments in its Warsaw office:
Counterparty Risk Analytics (CRA)
The 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 logics are implemented correctly in credit risk systems.
Credit and Obligor Risk Analytics (CORA)
The CORA team is responsible for covering enterprise-wide model development for wholesale and retail credit risk. CORA models are used to estimate advanced Basel III regulatory capital parameters and Global Systemic Stress Testing.
On the retail side, CORA plays an oversight role on Basel III exception adjustments and Basel III model performance. Additionally, CORA provides support for Retail Risk Weighted Assets (RWA) Stress Testing for CCAR.
On the wholesale side, CORA models produce the CCAR and ICAAP estimations. Other wholesale models cover loan loss reserves (IFRS 9/ CECL), cost of credit, obligor risk ratings (debt rating models), liquidity stress testing, RWA stress testing, and market-based default and downgrade risk models.
CORA is also responsible for approval of all risk rating policies and processes for wholesale portfolios.
Market Risk Analytics (MRA)
The MRA team is responsible for developing and maintaining market risk models used for both risk management and regulatory capital purpose. These models currently include Value-at-Risk (VaR), Stressed VaR (SVaR), Incremental Risk Charge (IRC) for trading book migration and default risk, and Comprehensive Risk Measure (CRM) for credit correlation trading.
The team also maintains the Citi Market Risk Exposure Specification, which provides a set of consistent risk sensitivity measures across the firm. In performing the ongoing calibration of the market risk models, the team also specifies, collects, verifies, and maintains historical time series of the market factors. Additionally, the team’s mandate includes obtaining approval on market risk models for Basel regulatory capital calculation, preparing Citi for future regulation changes (e.g., Fundamental Review of the Trading Book), and provides quantitative analyses and support to Market Risk Managers.
Risk Capital Analytics (RCA)
The RCA team is responsible for defining the overall framework and principles of Risk Capital (RC) across market risk, wholesale and retail credit risk, pension risk, and ALM risk. RC is a firm-wide metric to measure economic capital usage at the consolidated group as well at the detailed business unit level. It is reported to regulators and the Board as a key capital adequacy metric for Citi and its major legal entities. RC is also used extensively to set risk limits and to assess the risk-adjusted profitability of large transactions.
Regional Stress Testing
The Regional Stress testing team focusses on the end-to-end delivery of non-CCAR related cross-risk-stripe regulatory stress tests and ICAAPs in the Europe, Middle East, and Africa (EMEA) region. The EMEA region houses some of the most sophisticated trading and banking books outside of the Citibank North America branch network, and the team specialises in virtual collaborations with in-country Risk/Finance, and infrastructure teams globally to overlay the local regulatory framework, local accounting standards, and emerging regulatory expectations on the central core capabilities provided by Citi.