Whole Credit Sales Stress Tester - Syntricate Technologies : Job Details

Whole Credit Sales Stress Tester 388 Greenwich St, New York, NY 10013 (3 days onsite - Hybrid) 6+ Months Web Cam Interview $75/Hr on W2 Stress testing is a must have. Must Haves:

• 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. Tableau, Python, R)
• Proficient with MS Office suite.
• Past experience working on stress testing, model analytics, benchmarking and review & challenge function.
• Knowledge on scenario design, sensitivity shocks and risk identification process
• Good interpretations skills to convey complex quantitative methodology in simple terms.

General Notes Top Skills Ranked :

• Quantitative Skills (stress testing & model validations)
• Finance Knowledge (wholesale credit knowledge)
• Technical Skills (tableau and python for data manipulation)

Prior Risk experience (stress testing) Whole Sale Credit experience (or consumer credit) Need someone who understands the business and understands the implications of the specific numbers used by the business Running monthly stress testing and needs someone who is strong technically Should understand how stress testing model works and what the numbers generated mean Combination of Math-focused, Programmer, and Finance background Understand the business, stress testing, and how to analyze results Should understand how the modeling works (what's driving #'s up or down) Need skills to build analytical tools and build those in-house Bachelor's Degree level education Responsibilities:

• Execute periodic stress testing exercises to monitor WCRs 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.
• Perform quarterly gap assessment between scenario coverage and material risk inventory.
• 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. Tableau, Python, R)
• Proficient with MS Office suite.
• Past experience working on stress testing, model analytics, benchmarking and review & challenge function.
• Knowledge on scenario design, sensitivity shocks and risk identification process
• Good interpretations skills to convey complex quantitative methodology in simple terms.

Education:

• Bachelors/University degree or equivalent experience, potentially masters degree