Decision Science Lead - SAS - London
Job Title: Decision Science Lead
Salary: to £80,000 plus bonus and benefits
An opportunity to join an expanding Decision Science team, leading analysts & senior analysts in modelling and segmentation activities across credit risk and marketing.
- Develop scoring models and segmentation tools for the core lending decisions, including new customer accounts and existing customer management, and key business areas including collections, risk and response models for marketing’s acquisitions and cross-sell activities.
- Drive modelling and segmentation for core lending strategies across the business, including account level profitability, collections, fraud, and authorisations.
- Document, monitor and maintain all models developed, ensure all models are accurately implemented, re-develop models as necessary.
- Liaise with internal customers to ensure best use of models within the business.
- Project management of core decision science projects
- Manage external credit bureau relationships
- Define the modelling approach and strategy
- Develop targeted models to drive value in key business areas
- Research and understand all data sources available and their respective power
- Build appropriate models using SAS regression, decision trees, reject inference, define sample windows, good-bad definitions, data classing and other techniques as appropriate
- Apply population segmentation techniques, validate models for performance and stability through time
- Maintain awareness of relevant legislation, credit reference and customer data rules
- Complete documentation for all scorecard development and decisioning
What do you need to apply?
- At least 5 years’ experience in statistical modelling and analysis using regression and other statistical techniques within a financial services environment, ideally credit risk or marketing within retail banking.
- Proficiency using SAS, SQL and Office products, in particular Excel and PowerPoint, and the ability to combine these technical skills with a solid commercial awareness.
- Excellent communication skills, with experience presenting to senior business members.
- A degree (2:1 or better) in a quantitative subject such as Mathematics, Statistics or Operations Research