Scope:

The role is part of a modeling team attached to the newly formed regional lending strategy unit. The team’s goal is to utilise analytics extensively, to systematically ‘out-think’ and ‘out-execute’ the competition.  The unit as a whole will be responsible for portfolio shaping across the West governance (Americas, Europe, Africa, Middle East and South Asia), with the principal aim of reducing risk and maximising profit through enhanced understanding of income volatility.  Complex business problems across the credit risk life-cycle will be deconstructed, and decision optimisation will be used to enhance our earning potential… 

Responsibilities:

• Decompose complex business problems, utilising decision analysis methodologies to enhance profitability and reduce earnings volatility
• Design, plan and manage data driven statistical modeling projects for key international portfolio’s
• Manage, and implement decision optimisation projects across the credit life cycle. 
  • Development, and implementation of scorecards, credit risk models, credit grading systems, pricing and profitability models.
  • Assist and support the development and enhancement of credit risk measurement tools and risk reporting/analysis across all exposures
  • Provide statistical input to the development of scorecards, credit grading systems, pricing and profitability models.
  • Contribute to the management of activities outsourced to third parties.
• Lead the analytic components of the modeling project, making key analytic decisions including modeling approach, data integrity, population segmentation, model review and result presentation.
• Adhere to the necessary controls for the development, validation, implementation and maintenance of models.
• Input to the development of risk grading IT solutions to ensure the accuracy of risk measurement across the portfolio and the capture and organization of necessary data.
• Contribute to the work of project teams as to the appropriate use of risk models and scorecards in new market initiatives.
   

Skills / Knowledge:

• Specialist skills in analytical modeling
  • Direct working experience with statistical modeling, optimisation or other quantitative analysis fields
  • Qualified to degree level in statistical or mathematical/scientific discipline or previous modeling experience is a necessity.  Preferred = MS or PhD in Statistics, Mathematics, Operations Research or other related areas.
  • Experience with statistical modeling and analytic techniques such as OLS and logistic regression, univariate and multivariate statistical analysis, CART and/or CHAID, clustering, neural networks, and survival analysis.
  • Experience of decision analytics.  Including sensitivity analysis, Monte Carlo Simulation
  • Credit scoring experience strongly preferred
  • Proficient using scorecard building tools.  Model Builder for Predictive Analytics (Fair Isaac) and/or Enterprise Miner (SAS).  
  • Proficient SAS programming skills and strong experience with: DATA step data manipulation with arrays, do-loops, and merges; SAS Macro language, SAS/GRAPH, PROC SQL experience.  SAS Certified Base Programmer will be considered a plus.
• Strong analytical skills and understanding of quantitative and statistical analysis.
• Strong project management skills, able to handle complex projects in a multi-tasking environment and meet deadlines with quality results.
• Strong logical and analytic skills to apply statistical analysis to solve business problems
• Knowledge of financial industry preferred – but not necessary
• Strong interpersonal skills, able to liaise with Senior Management and colleagues