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Risk Management – Model Risk Associate – Wholesale Credit Loss Forecasting C&I

Risk Management – Model Risk Associate – Wholesale Credit Loss Forecasting C&I

CompanyJP Morgan Chase
LocationNew York, NY, USA
Salary$Not Provided – $Not Provided
TypeFull-Time
DegreesBachelor’s
Experience LevelMid Level

Requirements

  • A Degree in a quantitative field such as Math, Physics, Engineering, Economics or Finance is required.
  • 2 plus years of experience in a quantitative or modeling role.
  • Strong communication skills verbally and particularly in writing, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports
  • Experience with large data sets is required
  • Understanding of Python, R, or equivalent
  • Deep understanding of statistics / econometrics
  • Risk and control mindset: ability to ask incisive questions, assess materiality of model issues, and escalate issues appropriately

Responsibilities

  • Set standards for robust model development practices and enhance them as needed to meet evolving industry standards
  • Evaluate adherence to development standards including soundness of model design, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics
  • Identify weaknesses, limitations, and emerging risks through independent testing, building of benchmark models, and ongoing monitoring activities
  • Communicate risk assessments and findings to stakeholders, and document in high quality technical reports
  • Assist the firm in maintaining (i) appropriateness of ongoing model usage, and (ii) the level of aggregate model risk within risk appetite

Preferred Qualifications

  • A Ph.D. or Master’s degree in a quantitative field such as Math, Physics, Engineering, Economics or Finance is a plus.
  • Knowledge of credit loss forecasting models for C&I portfolios is desirable. Additionally, knowledge of credit models such as Merton type structural models is a plus.
  • Some knowledge of pricing models is useful.