Senior Statistical Analyst

  • Location


  • Discipline:

    Credit Risk & Analytics

  • Job type:


  • Salary:

    £50,000 - £60,000

  • Consultant:


  • Email:


  • Job ref:


  • Published:

    almost 3 years ago

The Senior Statistical Analyst is an applied statistician who builds and maintains predictive statistical models using a variety of advanced analytic tools, frameworks, and approaches.

Key Responsibilities:

  • Build new predictive statistical models, maintain existing models, and focus relentlessly on identifying new sources of data
  • Provide analytic support to the operational channels including (a) general statistical expertise, (b) project leadership involving complex problem solving, and (c) identifying new opportunities to use predictive modelling in service to revenue and cost targets
  • Serve as an analytic coach and/or mentor to peers and junior staff within the Decision Science department and the operational groups
  • Research and development activities, including both internal and external research, focused on subprime credit dynamics, financial distress, and a variety of consumer intelligence topics
  • 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 visualization, and experimental methods

Key Requirements:

  • Master’s degree (or higher) in statistics, mathematics, or a quantitative science, with significant coursework in statistics and experimental design
  • Expertise with formal statistical methodologies, including strong knowledge of two or more of the following: logistic regression, generalized linear models, categorical data analyses, ANOVA and regression models
  • Proficiency with base SAS and SAS/STAT, or a related technology (e.g., R, Matlab, or IDL)
  • Familiarity with longitudinal and outcome-based modelling, the logic of credit scoring, and NPV and IRR analyses
  • Proficiency with MS Office, particularly Excel and PowerPoint