Data Scientist - Fraud Analytics Models (Public Sector)

1-year contract, renewable Government project Hybrid work arrangement Role Overview The Data Scientist will join the Fraud Analytics Models (FAM) team within the Data Science and AI Division (DSAD).

supports the maintenance and expansion of FAM 2.0, which detects misuse of public training grants. Key priorities include addressing the backlog of methodology and threshold reviews, building and operationalising the FAM 2.0 Technical Dashboard, and assessing how new schemes can be progressively included in FAM 2.0’s fraud-risk coverage. The successful candidate will contribute to reliable fraud-risk analytics, clear methodologies and sustainable implementation, while helping build DSAD’s in-house capability.

Key

Methodology and threshold reviews: Review and recalibrate FAM 2.0 methodologies and thresholds for prioritised backlog items. This includes back-testing, impact assessment, analytical specifications, validation approaches, gap analyses and documentation. Risk model enhancement: Translate business, policy and scheme requirements into changes to fraud-risk scenarios, indicators, features, thresholds and analytical logic.

Technical Dashboard development: Build and enhance monitoring of model performance, including precision and recall, data drift and concept drift. Develop alert logic and visualisations, and support deployment. Design performance measures that account for delayed or incomplete investigation outcomes.

New scheme assessment: Assess ne