Fraud Risk Analytics Scientist – Public Sector

NEXBRIDGE RECRUITMENT PTE. LTD.; Singapore; Sur place; SGD 90 000 - 140 000; Plein temps

Résumé du poste

Nexbridge Recruitment Pte. Ltd. is seeking a data scientist to recalibrate risk models, develop fraud indicators and monitor model performance. The role requires turning business requirements into analytical logic and maintaining reproducible analyses.

You will work across data science, engineering and business teams to ensure rigorous data handling and clear documentation. 3+ years in analytics and a quantitative degree are preferred.

Qualifications

• Degree in quantitative field such as Data Science, Statistics or Mathematics.
• Minimum 3 years hands-on data science, analytics or model validation.
• Proficiency in Python and SQL for data extraction and analysis.
• Experience building or validating predictive/fraud-detection models.
• Ability to translate requirements into analytical specifications and rules.
• Experience with large datasets, data quality and data lineage.

Responsabilités

• Review and recalibrate FAM 2.0 models, including back-testing and documentation.
• Translate requirements into fraud-risk indicators and logic.
• Build monitoring for model performance, data drift and concept drift.
• Design performance measures for delayed or incomplete outcomes.
• Assess schemes against risk taxonomy and document changes.
• Maintain methodology records and communicate findings to stakeholders.
• Produce reproducible code, analyses and documentation.

Connaissances

Model validation

Fraud analytics

Data analysis

Communication

CI/CD / MLOps

Data quality

Problem solving

Python

SQL

Exploratory analysis

Formation

Quantitative degree (Data Science / Stats / Math / CS / Eng / Econ)

Outils

Python

SQL

Tableau

Spark/PySpark

AWS Redshift

AWS Glue

Description du poste

Nexbridge Recruitment Pte. Ltd. is seeking a data scientist to recalibrate risk models, develop fraud indicators and monitor model performance. The role requires turning business requirements into analytical logic and maintaining reproducible analyses.

You will work across data science, engineering and business teams to ensure rigorous data handling and clear documentation. 3+ years in analytics and a quantitative degree are preferred.