DETAILS:

Domain: Banking

Position: Quantitative Risk Analyst

Duration: 6 Months (Possibility of extension or conversion)

Location: Irving, TX (Hybrid 3 Days/Week Onsite)

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