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Senior Vice President, Model Analysis Group

Job Req ID 21331370 Primary Location Warsaw, Poland Job Category Risk Management
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The Model Analysis Group (MAG) is a growing team within Risk Modeling and Analytics (RM&A). It is responsible for all post model development analytics relating to models developed by RM&A teams, as well as the Capital and Stress Testing (C&ST) teams, including Ongoing Performance Assessments (OPA), Annual Model Reviews (AMR), and Revalidations.

Members of the MAG will be actively involved in different aspects of the model lifecycle.  A typical model goes through different stages: design, calibration, testing, documentation, validation, implementation, monitoring and back to re-design and re-calibration when relevant assumptions change or monitoring indicates performance issues.  OPAs and AMRs are critical parts of the model lifecycle to determine model performance (model use and monitoring) that can trigger model re-design or re-calibration by identifying critical issues.

Thus the job is related to a critical stage/decision point; essentially whether or not the model can still be used, which in turn has a material impact on resources, timelines, and deliverables.

Key mandates also include driving productivity enhancements in Model Analysis through innovation.  The MAG will leverage cutting edge software and technology to reimagine the way we currently execute on this crucial phase of the model lifecycle, to the benefit of our partners, including model sponsors, developers, and Model Risk Management.

As the MAG spans all RM&A and C&ST models, members of the MAG will have the opportunity to become well-versed in multiple risk stripes, with such skills training enhancing their mobility and growth potential within QRS and the larger Risk organization.

Reporting relationships:

The position will work very closely with others in the MAG, including the Head of MAG who reports to the head of RM&A.  RM&A and C&ST develop risk analytics for use by Risk, Finance and Product and Client Coverage teams on a global basis. The head of RM&A reports to the Finance Chief Risk Officer who in turn reports to the Citi Chief Risk Officer.

Key responsibilities:
This is a Team Lead role.In addition to executing on deliverables the candidate will be responsible for managing and mentoring a Team to ensure the quality and timeliness of deliverables to our partners.The candidate will work closely with the Head of the Model Analysis Group (MAG) and other Team Leads to attract and retain talent, provide career growth opportunities to members of the MAG and work collaboratively with all of the MAG to help deliver on the overall book of work.


Partners include various working groups, model developers, risk managers, business clients, model validators, Risk IT, internal and external auditors, and regulators.  Engage with partners, as appropriate, to:

  • Develop and implement methodologies, algorithms and diagnostic tools for testing model robustness, stability, reliability, performance and quality control of modeling data.

  • Conduct on-going model performance analysis,

    • Discover, understand and quantify model limitations,

    • Provide comprehensive interpretations, explanations and conclusions,

    • Work with partners to resolve model issues

  • Enhance efficiency and effectiveness of implementation of post model development analytics

    • Automate and consolidate ongoing model analysis and the annual model review process across different models,

    • Migrate analytics to a production environment as appropriate

  • Support various tasks in response to regulatory and internal risk management requirements.

Develop, maintain and enhance technical documentation including project plans, model descriptions, mathematical derivations, data analysis, process and quality controls.

More specifically, develop methodologies, algorithms and diagnostic tools for testing model robustness, stability and performance for the following risk stripes:

  • Risk Capital (RC)

    • RC is a firm-wide metric to measure economic capital usage at the consolidated group and CBNA levels as well at the detailed business unit level. It is reported to regulators and the Board as a key capital adequacy metric for Citigroup and its major legal entities (MLE). RC is also used extensively in the ICG, CCB and GCRM to set risk limits and to assess the risk-adjusted profitability of large transactions.

  • Enterprise Stress Testing

    • Firm wide stress testing methodologies are widely used in Citi’s identification and measurement of tail risks to assess potential vulnerabilities and capital adequacy. These are foundational elements used in the firm’s risk-return metrics, Board and regulatory reporting, and limit setting frameworks at both Group/CBNA level and certain business/geographic segments.

  • Economic Forecasting

    • The Economic Forecasting Team is responsible for forecasting firm wide macroeconomic and financial variables that are critical inputs to a variety of corporate stress tests, loan loss reserves and financial planning model. These includes, CCAR, MCST, Mid-Year-Forecast for Corporate Planning, Annual Corporate Operating Plan, ICAAP, forward looking indicator (FLI) forecast for IFRS, CECL and Global Systemic Stress Tests (GSST's).  Models include both macro-econometric, and financial econometric models.  Testing includes back testing, ex-post and ex-ante performance testing, model stability testing, etc.

Other areas covered by the MAG include:

  • Market Risk Analytics:

    • Analysis for market risk models includes, but is not limited to, backtesting and profit attribution analysis (PAA) on hypothetical portfolios for credit, FX, rates and mortgage products.

  • Counterparty Credit Risk:

    • Understand models (pricing model and simulation model) and the model usages in various applications (CCR capital requirement calculation under Basel III, accounting CVA and internal credit exposure limit monitoring)

    • Understand systems, data flow, data definition and data requirement for various trading products. Utilize this knowledge to perform various analyses to meet risk managers and business needs

  • Retail:

    • Retail models include Basel, Risk Capital, Internal Stress Testing (GSST) and related models.  These models are applied to all delinquency managed portfolios across the globe and cover upwards of $320 billion in exposure. 

  • Foundational Risk & Reserves (FR&R)

    • FR&R models include loss likelihood and severity methodologies and applications, including methodologies used for CECL and IFRS 9, as well as foundational measures of risk (PD, LGD, CCF).

  • Credit and Risk Rating Analytics (CRRA)

    • CRRA models include one-year probability of default models and Expert Judgment Risk Rating Methodologies used for low data / low default portfolios.

  • Wholesale Credit Stress Testing (WCST)

    • Includes CCAR and ICAAP models


  • 8+ years’ experience.  Fewer years’ experience considered with advanced degrees.

  • Educated to a postgraduate level, with an excellent academic record in a mathematical and quantitative field (e.g. mathematics, physics, statistics, engineering, economics, finance, financial engineering, etc.). Masters or Ph.D. is strongly preferred.

  • Solid programming skills and experience with statistical and data analysis, modeling techniques and numerical implementations.  More specifically experience in C/C++, Java, SAS, Python, R and Perl, shell scripts, UNIX, VBA and basic database skills in either Oracle or Sybase/SQL.

  • Experience in developing and maintaining detailed technical documentation for models, model validation, project plans and processes preferred.

  • Ability to meet deadlines for product deliverables in a timely, proactive and entrepreneurial manor.

  • Strong written and verbal communication skills, and ability to discuss technical issues with partners.

  • Strong interpersonal skills and the ability to foster a collaborative environment

  • Organized, disciplined and detail oriented with sound problem-solving skills, and the ability to think creatively.

  • Keen interest in banking and finance, especially in the field of Risk Management.

  • Experience in quantitative finance or a related field, analyzing large and complex data sets, data reliability analysis, quality controls and data processing preferred.

  • Experience of one or more of the following is an advantage but not essential: derivative pricing and exotic products; risk management practices and procedures; numerical methods; Monte Carlo simulations; statistical hypotheses testing; banking-book products, risk analytics for wholesale stress testing for credit portfolios, credit risk modeling and risk management or related areas.

  • Basic understanding of financial products in the trading book (equity, fixed income, derivatives, etc.) and their market drivers (price, interest rates, implied volatilities).  Basic understanding of the Value-at-Risk (VaR) model and historical simulation framework.

  • Basic understanding of macroeconomics, monetary economics and econometrics, statistics, time series analysis and Monte Carlo simulations.  Familiarity with continuous time models and stochastic processes.  

We Offer:

  • Opportunity of professional development in the international and well-established company

  • Learning opportunities and challenging assignments in which you can utilize your knowledge

  • Competitive social benefits

  • Chance for a career evolution within Citi business structures


Job Family Group:

Risk Management


Job Family:

Risk Analytics, Modeling, and Validation


Time Type:


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