Data Scientist

Your tasks

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.

Requirements

Experience: 3–5 years of hands-on experience in data science, advanced analytics,

model validation, fraud/risk analytics or programme analytics.

B. Technical & Professional Competencies

• Strong hands-on proficiency in Python and SQL for data extraction,

transformation, exploratory analysis, with experience building reproducible

analytical workflows.

• Hands-on experience developing, validating or enhancing predictive, risk-scoring,

fraud-detection or anomaly-detection models, including feature development,

back-testing, threshold calibration and performance evaluation using measures

such as precision, recall and related trade-offs.

• Experience translating business, policy or operational requirements into

analytical specifications, model logic, indicators, rules or measurable risk

hypotheses.

• Experience working with complex, large-scale datasets, including assessing data

quality, tracing data lineage, investigating anomalies and documenting analytical

assumptions.

Other

Work location- Paya Lebar The Data Scientist is embedded within the Data Science and AI Division (DSAD), working