Full job descriptionContract Credit Risk Modeller*£560-£640 per day
*Inside IR35
*Fully remote
*Three-month contract
The companyHarnham is partnering with a leading financial data and analytics organisation to recruit a hands-on Credit Risk Modeller for an initial three-month engagement.
You will join its UK Product Analytics and Innovation team, supporting the rapid development of a new credit-risk product.
The roleYou will independently build a point-of-application credit risk scorecard from raw data through to a validated, production-ready MVP.
Your responsibilities will include:
*Ingesting, joining and cleaning complex customer and credit datasets
*Constructing development samples and defining observation and performance windows
*Establishing appropriate good/bad definitions
*Engineering characteristics and treating missing and special values
*Performing monotonic binning, Weight of Evidence and Information Value analysis
*Developing an interpretable logistic-regression scorecard
*Completing feature selection, model tuning and points-based score scaling
*Validating the model using measures such as Gini, KS, AUC, PSI and out-of-time testing
*Producing clear technical documentation and supporting production implementation
Your skills and experienceThe successful candidate will have:
*Personally built and deployed at least two end-to-end consumer or commercial credit scorecards
*Advanced hands-on Python experience within credit-risk modelling
*Strong SQL skills and the ability to prepare complex modelling datasets independently
*Practical experience with WoE, IV, binning, logistic regression and score scaling
*Experience defining modelling samples, performance windows and credit outcomes
*A track record of implementing scorecards within lending, underwriting, collections or credit decisioning
*The ability to write custom transformations and debug Python logic independently
*Experience delivering models within regulated financial-services environments
*Availability to begin immediately or at short notice
Experience with credit-bureau, SME, commercial, Companies House or Open Banking data would be beneficial. GCP and BigQuery experience is also desirable, although other cloud platforms will be considered.
Candidates should be prepared to discuss a previous scorecard build in granular detail during the interview, including feature choices, binning decisions, model trade-offs, validation results and their individual coding contribution.