Credit Risk Statistical Modeller AVP/VP

  • GBP0.00 per annum
  • London, England, United Kingdom
  • Permanent, Full time
  • Morgan McKinley
  • 26 Aug 16

Global investment bank seeks AVP or VP level Quant Analysts as part of their expanding wholesale credit risk quant modelling team

The team develops models for capital (Basel), impairment (IAS39/37, IFRS9), and stress testing (CCAR, PRA, EBA). Model outputs are utilised across a range of risk metrics, including RWA, pricing, Economic Capital, and for credit sanctioning.

Overall purpose of role

  • Lead the development of new models and manage junior members of the team.
  • Develop, document, and calibrate credit risk models in line with regulatory requirements, e.g. Basel, IFRS9
  • Support user understanding and investigate ad hoc queries
  • Enhance model management through automation and development of new approaches

Key Accountabilities

Develop credit risk models (60%)

  • Develop new credit risk models, managing the development through approval
  • Validate performance of new models
  • Document new models to required standards

Manage stakeholders (30%)

  • Work with other parts of the Bank to ensure understanding of model applications, limitations, uses and abuses
  • Maintain open dialogue with other modellers and validation teams on model developments and reviews
  • Address modelling queries from user community, looking at specific customer ratings and their calculation

Manage junior team members (10%)

  • Day to day management of junior members of the team
  • Lead direction of work for projects

Stakeholder Management and Leadership

  • Strong stakeholder management skills, with experience from complex projects
  • Good project and people management skills; ability to motivate team and deliver within tight deadlines

Decision-making and Problem Solving

  • Post graduate degree in a quantitative discipline, Mathematics, Statistics, Physics, Engineering, Econometrics
  • Very strong knowledge of statistics, e.g. regression analysis, reject inference, decision trees, cluster & time-series analysis
  • Strong numerical programming ability using a range of languages (R, C++, Python); working experience with SQL
  • Track record of producing high quality written communication including results of research and presentations for technical and non-technical audiences
  • Experience of developing and applying statistical models within credit risk domain
  • Understanding of the quantitative techniques used in developing and validating PD, LGD, and/or EAD models

Risk and Control Objective

Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays Policies and Policy Standards

Person Specification

  • Ability to quickly adapt to new environments & systems
  • A keen eye for detail
  • Self-starter: motivated and disciplined
  • Able to work in isolation and within a team environment, as required

Morgan McKinley is acting as an Employment Agency in relation to this vacancy.