Data Scientist - Public Sector Fraud Analytics

NTT SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

NTT SINGAPORE PTE. LTD. is seeking a Data Scientist embedded in the Data Science and AI Division (DSAD) as part of the Fraud Analytics Models (FAM) team. You will help maintain and expand FAM 2.0, develop the technical dashboard, and assess how new schemes can join coverage.

The role emphasizes reliable fraud-risk analytics, clear methodology, and sustainable implementation, with responsibilities spanning model validation, threshold review, governance, and knowledge transfer.

Qualifications

• 3-5 years of hands-on experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics.
• Strong Python and SQL skills; experience building reproducible analytical workflows.
• Experience translating business, policy or operational requirements into analytical specifications and model logic.

Responsibilities

• Review and recalibrate FAM 2.0 model methodologies and thresholds for backlog items; back-testing, validation, and documentation.
• Translate business requirements into fraud-risk scenarios, indicators, features and thresholds.
• Build and enhance monitoring for model performance, data drift, and alert logic; design performance measures.
• Assess new schemes' structures, eligibility rules, and known fraud risks; map to FAM 2.0 risk taxonomy.
• Maintain clear methodology and change records; communicate findings to programme owners and stakeholders.
• Produce reproducible code and documentation throughout the engagement.

Skills

Python

SQL

Model validation

Fraud analytics

Data workflows

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or related field

Tools

Python

SQL

Tableau

Spark

PySpark

AWS Redshift

AWS Glue

MLOps

CI/CD

Job description

NTT SINGAPORE PTE. LTD. is seeking a Data Scientist embedded in the Data Science and AI Division (DSAD) as part of the Fraud Analytics Models (FAM) team. You will help maintain and expand FAM 2.0, develop the technical dashboard, and assess how new schemes can join coverage.

The role emphasizes reliable fraud-risk analytics, clear methodology, and sustainable implementation, with responsibilities spanning model validation, threshold review, governance, and knowledge transfer.