This Job Vacancy has Expired!

Director Quantitative Model Validation

Posted on Jan 27, 2019 by Ashton Lane Group

Washington, WA 20001
28 Nov 2018
Annual Salary


  • Design and lead model validation projects, in an analytic capacity
  • Evaluate the landscape of tools to understand what will unlock new capabilities and performance and what is just a distraction
  • Leverage extensive, deep technical knowledge and team leadership skills to drive the development of modeling solutions and data-driven recommendations and outcomes
  • Manage the assessment of the methodologies and processes used by modeling teams to develop and manage their models, and identifying potential weaknesses and the associated materiality of the risk
  • Lead the development of project plans, setting and managing expectations, and delivering results through self and/or others
  • Guide the benchmarking of model methodologies and performance by developing alternative models
  • Analyze complex data to identify data integrity issues
  • Research and enhance industry practices related to model methodologies
  • Manage the documentation of validation processes and results


  • 5+ years' experience building or validating Commercial / Wholesale models
  • Current / Recent experience within a top tier management consulting firm working on AI, Machine Learning, or RPA strongly preferred
  • Experience with credit risk stress testing models and internal risk rating model development are highly desirable
  • Familiarity with R and/or Python.
  • Team player with strong interpersonal and communication skills
  • Advanced degree in a quantitative discipline (e.g., statistics, physics, math)

For immediate consideration, please forward resume and contact details to:

Ashton Lane Group is a boutique executive recruitment firm serving the Banking, Insurance, and Alternative Investment sectors. For the latest opportunities, visit

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Senior position supporting the validation of loss forecasting, stress testing and Basel-related models for a large financial institution

Reference: 633677090