Applied Modelling Analyst

  • Location


  • Discipline:

    Credit Risk & Analytics

  • Job type:


  • Salary:

    £30,000 - £38,000

  • Consultant:


  • Email:


  • Job ref:


  • Published:

    almost 3 years ago

This is an exciting opportunity to join a team that partners broadly within the organisation and influences the company’s operational, analytic, and financial strategies. Moreover, this role is part of a thriving, pan-European modelling community devoted to using the best elements of applied and theoretical work from statistics, psychology, management science, and behavioural economics to understand the fundamental drivers of consumer financial behaviour.

Key Responsibilities:

  • Independently summarise analysis results for direct managers and colleagues and explain the rationale for specific analytic decisions expertly and clearly
  • Develop expertise around different aspects of business model and approach, and demonstrate the ability to lead projects within specific functions
  • Maintain and re-estimate statistical models as appropriate
  • Active participation in the department’s Modelling Symposium, which includes discussion of theoretical and methodological papers, peer-review of ongoing projects, topical seminars, and ongoing training focused on effective communications, data visualisation, and experimental methods

Key Requirements:

  • Undergraduate degree in a subject containing formal statistical training, such as Statistics, Mathematics, Econometrics, Sciences, Psychology or similar, and a masters (or PhD) in a subject containing formal statistical training.
  • Basic working knowledge (or better) of a structured programming language (Base SAS, SAS Enterprise Guide, R, Python, Matlab etc.) likely obtained through prior work experience conducting data analysis, reporting, and/or modelling
  • Knowledge of formal statistical methodologies, including some of the following: logistic regression, generalised linear models, categorical data analyses, ANOVA, and regression models
  • Prior exposure to NPV calculations, IRR logic, and/or asset valuation & cash flow estimation approaches would be advantageous