Data Scientist - #1730

Role Overview The Data Scientist is embedded within the Data Science and AI Division (DSAD), working as part of the Fraud Analytics Models (FAM) team. The role will support the maintenance and expansion of FAM 2. 0, which detects misuse of public training grant.

This includes addressing the methodology and threshold review backlog; building and operationalising the FAM 2. 0 Technical Dashboard; and assessing how new schemes can be progressively brought within FAM 2. 0's fraud-risk coverage.

The candidate is expected to contribute to reliable fraud-risk analytics, clear methodology and sustainable implementation and to build up in-house capability along the way.

Key Responsibilities

• Methodology and Threshold Review: Review and recalibrate FAM 2.0 model 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 Build: Build and enhance monitoring for model performance (precision, recall), data drift and concept drift, including alert logic, visualisations and deployment support. Design performance measures that account for delayed and incomplete investigation outcomes.

• New Scheme Assessment: Assess new schemes' structures, eligibility rules, claims processes and known fraud risks. Map relevant patterns against the existing FAM 2.0 risk taxonomy and recommend how each scheme can be brought into coverage.

• Governance and Stakeholder Engagement: Maintain clear methodology and change records. Communicate findings, trade-offs, dependencies and recommended actions to programme owners, FAM stakeholders, engineers and management.

• Documentation and Knowledge Transfer: Produce reproducible code, analyses and documentation throughout the engagement. Requirem