Description

Job Description:
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

Education

Bachelor’s/University degree