Risk / Stress Testing Analyst

3 days ago


Irving, United States Open Systems Technologies Full time

Risk / Stress Testing Analyst


**python coding skills

• SVP level

• Support stress testing efforts and analyze the numbers

• Risk experience (CCAR, CECL, stress testing) required

• Wholesale credit or consumer credit required

• Heavy analytics

• Financial / banking clients required

• Not seeking a quant resource, pure programmer, or straight finance professional. Combo of all 3

• 3 days onsite/week

• 8am-6pm EST


Key Responsibilities:

• Execute monthly stress testing exercises to monitor WCR's risk appetite and identify vulnerable areas

• Cover key process of rapid stress testing, overlays

• Provide analytics support to stress test models in wholesale products, connect the stress testing output to model drivers

Other Responsibilities:

• Build tools & analytical capabilities to support outcome analysis, loss forecasting reports and what if analysis

• Gather and analyze portfolio and macro-economic data to assess potential impact on business performance and integrate the trends to the portfolio loss forecast

• 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

• Research on 3rd party data, loss history and alternative models to build inventory of benchmarks

• Contribute and refine current model performance monitoring process to interpret model output and identify opportunities for future improvements


Qualifications:

• 5+ years' experience in stress testing (CCAR/DFAST), CECL, or loss forecast model development

• 5+ years' experience with data analytical tools like Python or R

• Sound knowledge of C&I and CRE loss forecast modeling analytics, PD/LGD/EAD models, experience in HFS/FVO is preferred

• Demonstrated experience of building analytical tools to support the analysis of loss forecasting results, using tableau, Excel, R shiny or Python

• Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis.

• Proficient with MS Office suite, Word/Excel/PowerPoint.

• Knowledge on scenario design, sensitivity shocks and risk identification process

• Good interpretations and communications skills to convey complex quantitative methodology in simple terms


Education:

• Bachelor's/University degree or equivalent experience, potentially master's degree in Economics, Finance, or quantitative majors


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