Job Family Group:
- Citi is of the world's largest, most analytically sophisticated financial service providers with activities spread over 50+ countries. Expertise in quantitative analysis is central to our success in all these markets. Our modelers thrive in a culture of mutual respect, excellence and innovation. We have several opportunities available for top-notch quantitative professionals.
Citi's Economic Forecasting Team (EFT) under Quantitative Risk and Stress Testing (QRS); a global risk function is seeking to add a Senior Financial Economist/Econometrician who would be expected to provide thought leadership in designing, developing and executing statistical and econometric methods for forecasting thousands of financial variables. The forecasts of these variables are used as inputs by the firm's entire suite of stress testing exercises involving the credit book, market and trading book, counterparty risk, liquidity, operations, stressed VaR and risk weighted assets. The suite of stress testing deliverables are BHC Stress Tests, Regulatory FRB CCAR Scenarios, Annual Corporate Plans, CECL and IFRS-9. The teams current coverage of financial variables includes FX, sovereign rates, swap rates, interest rate volatilities, credit spreads, CDS, bond prices, implied and realized volatilities, equities and commodity prices. This senior role would manage a small team of quantitative professionals. Critical to this role is to have subject matter expertise in thinking through the macro-financial linkages of many of the financial variables and identify key drivers of financial shocks.
- The incumbent will be responsible for developing financial forecasting models and provide a subject matter expertise and clearly communicate to stake holders, colleagues on model development, execution and assessment.
- Monitors ongoing economics, financial and banking trends that influence risks to the firm, overall financial industry and trends in the global economy, the U.S. macro-economy, key industry sectors, the markets for money, capital, commodities and foreign exchange, and economic and financial policy issues.
- Ability to take exogenous global financial market scenarios, identify key risk factors, determinants, and develop analytics and or models to conduct conditional forecasting, back-testing, forecast density and estimation.
- Interpret forecast output results and ensure forecasts results are consistent with scenario assumptions, model assumptions, statistical and econometric foundational assumptions.
- Conduct necessary forecast oversight to ensure historical data and forecast consistency.
- Articulate and disseminate rationale for forecasts based on macroeconomic and financial linkages, within the backdrop of countries, monetary and fiscal policy.
- Required Qualification:
- PhD/MS in Finance, Economics, Empirical Finance, Econometrics, mathematics, statistics or equivalent.
- 0-1+ years financial economist experience in a major financial, public or international institution.
- Expertise in macro-finance analysis, forecasting with a focus on empirical financial econometrics methods.
- Excellent verbal and written communication skills.
- Candidates must have experiences in one of the following programing languages SAS, MATLAB, R or Python programming environment.
- Previous experience in a role requiring managing/analyzing large data sets and presenting the data visually to senior management is highly desired.
- Background in graduate level time series econometrics, financial econometrics, empirical asset pricing, empirical finance, risk analysis, is essential to be successful in this role. Presumably these backgrounds should have been mastered using Hamilton (1994), Greene (2018), Tsay(2013), Alexander(2008), Campbell-Lo et.al (1997), Ferson(2019), Engle, Bali(2016), Cochrane(2005).
- Desired Qualifications
- 0-1 years or more experience in macroeconomic modeling as it relates to forecasting economic / market variables, credit risk, allowance for loan loss reserves etc. Exposure to model review and documentation standards is strongly desirable. Such background can be obtained on the job or through advanced academic preparation.
- A strong preference for CCAR and Stress Testing related exposure.
- Proficiency in Microsoft Office applications (Excel, PowerPoint, Word). Familiarity with statistical packages such as SAS, SAS/EG, SAS/ETS, SAS/Base is required. Knowledge of MATLAB, R is a plus. Knowledge of financial analysis, modeling, systems and reporting preferred.
- Understanding of business line drivers for a large size global financial institution.
- Skilled at articulating methodological issues in a manner that is understandable for non-technical stakeholders
- An understanding of basic SQL queries.
- Background and experience in consumer or commercial risk, especially forecasting models.
Risk ManagementJob Family:
Risk Analytics, Modeling, and Validation Time Type:
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