VP, Wholesale Stress Testing (Hybrid)

The Model/Anlys/Valid Officer is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.

Responsibilities:

• Perform quarterly gap assessment between scenario coverage and material risk inventory.
• Communicate and present the impact of scenario changes on model outputs to senior business leaders
• Execute periodic stress testing exercises to monitor WCR’s risk appetite and identify vulnerable areas.
• Provide analytics support to explain the stress test outcome for wholesale lending products.
• Partner with business units and risk managers to assess data availability and fit for purpose modeling approaches.
• Interact with model developers, model risk governance, business risk, internal audit.
• Leverage business / product expertise to evaluate and challenge the stress loss assumptions in hypothetical and historical stress scenarios.
• Gather and analyze portfolio and macro-economic data to assess potential impact on business performance and integrate the trends to the portfolio loss forecast.
• Research on 3rd party data, loss history and alternative models to build inventory of benchmarks.
• Develop deep expertise in stress testing methodologies and validate fit for purpose usage in BAU stress testing management.
• Contribute and refine current model performance monitoring process to interpret model output and identify opportunities for future improvements.
• Create a new scenario design capability leveraging existing models & data to translate emerging risk to economic scenarios, model inputs or portfolio shocks.
• Build tools & analytical capabilities to support outcome analysis, loss forecasting reports and what if analysis.
• Works with large datasets and complex algorithms to derive analytical insights, identify data quality issues and support trend analysis.
• Leverages big data to develop innovative deployable solutions.

Qualifications:

• 5+ years’ experience working in financial institutions.
• Sound knowledge of statistical modeling concepts and industry best practices; experience with econometric and statistical modeling or application risk scoring.
• Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis.
• Experience with analytical or data manipulation tools (e.g. Python, Tableau, R) Proficient with MS Office suite.
• Past experience working on model analytics, back testing, benchmarking and challenger function.
• Knowledge on scenario design, sensitivity shocks and risk identification process
• Good interpretations skills to convey complex quantitative methodology in simple terms.

Education:

• Bachelor’s/University degree or equivalent experience, potentially Masters degree

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In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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