Leading Financial Services Company s Commercial Bank contains an approximately $100B (exposure) loan portfolio that has grown by virtue of several acquisitions. It is a Commercial Portfolio of C&I, CRE, Financial Institutions lending, and various other specialty lending. As one of its top initiatives, the bank is updating its suite of statistical loss forecasting models for a series of critical processes, such as CECL, Capital allocation, and Credit decisioning.
Responsibilities and Skills:
Ownership of methodology development and parametrization of substantial components of Probability of Default, Loss Given Default, and Exposure at Default models in the wholesale portfolio risk suite, under the guidance of a senior manager
Understand technical issues in statistical modeling, including theoretical assumptions and methodology limitations, data pitfalls, model sensitivities, simulation approaches or scenario analyses for low-default portfolios, and applying these skills toward providing robust solutions to business problems
Communicate technical subject matter clearly and concisely in long-form writing of the model documentation and in short-form interactions in meetings with experts from various backgrounds, such as partner teams, senior management, model risk officers
Interface effectively with partner teams and business customers: understand the business needs, identify available data and its quality and governance, prepare analyses and draft materials for discussion of model component options and results, defend the theoretical robustness and practicality of the selected approach and outcome to oversight groups, support the implementation team, and conduct impact estimation
Identify opportunities to automate parts of model development and contribute to infrastructure, tool, or process improvement to enable efficiencies on the team
Balance several priorities at a time, for example contribute to re-calibration of one model while staying on top of business-as-usual processes such as annual reviews of model appropriateness, issue remediation, ad-hoc user questions, third party model audits, on another model, keeping their respective timelines in mind
Work on various ad hoc quantitative, modeling, and programming assignments using R or Python
Basic Qualifications:
Master s Degree in Statistics, Econometrics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Business, Technology or Physics
4 years experience in statistical or econometric modeling
Preferred Qualifications:
2-4 years of credit risk modeling experience for commercial bank, or portfolio risk modeling at an investment firm
Experience in underwriting, deal structuring, credit analysis, or investment portfolio management would be a plus
Professional qualifications (CFA, FRM, etc) would be a plus



* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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