The Model Analytics Group (MAG) is a growing team. It is responsible for all post model development analytics relating to risk models, 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 Analytics 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.
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:
Analysis for market risk models includes, but is not limited to, backtesting and profit attribution analysis (PAA) on hypothetical portfolios for all asset classes across the trading book.
Automating and consolidating ongoing model analysis and the annual model review process across different models to enhance efficiency.
Collaborating with model developers, market risk managers, model validators, and Risk IT to discover and resolve model issues and enhance existing implementation.
Supporting various tasks in response to regulatory and internal risk management requirements.
Counterparty Credit Risk:
Deliver on-going performance test including back-testing and other tests of EMEA legal entities CGML/CGME/CEP.
Produce high quality documentation of quantitative results, providing insightful narrative on stress scenarios and losses, in ICAAP document
Understand models (pricing/simulation/margin/aggregation 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, business and regulators’ needs.
Minimum of a Master’s degree in quantitative field (e.g. mathematics, physics, statistics, engineering, economics, finance, financial engineering, etc.) with 2+years of relevant experience.
Fewer years of relevant experience will be considered for candidates with higher academic qualifications and/or certifications such as a PhD, a second Master’s degree, CPA, FRM or CFA
Solid programming skills and experience with statistical and data analysis, modelling techniques and numerical implementations. More specifically experience in 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 multi-task, work well under pressure and committed to deliver under tight deadlines
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; trading-book products, risk analytics for wholesale stress testing for credit portfolios, credit risk modelling and risk management or related areas.
Basic understanding of macroeconomics, monetary economics and econometrics, statistics, time series analysis and Monte Carlo simulations. Familiarity with continuous time models and stochastic processes.
What we offer:
Work in a challenging area of the financial industry with one of the world's leading companies with exposure to variety of products, processes and controls
Cooperation with a high quality, international, multicultural and global team
Work in a friendly and diversified environment, appreciating differences in style and perspective and using them to add value to decisions leading to organizational success
Management supporting balanced and agile work
Attractive benefits package (Benefit System, medical care, pension plan etc.)
A chance to make a difference with various affinity networks and charity initiatives
Job Family Group:Institutional Trading
Job Family:Quantitative Analysis
Time Type:Full time
Citi is an equal opportunity and affirmative action employer.
Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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