Data Scientist | Contract

Key Responsibilities

• Review and recalibrate fraud analytics model methodologies and thresholds through back-testing, impact assessments, validation and gap analysis.
• Enhance fraud-risk models by translating business, policy and scheme requirements into risk indicators, features, detection rules and analytical logic.
• Develop and improve monitoring dashboards to track model performance, precision, recall, data drift and concept drift.
• Assess new schemes, identify potential fraud risks and map them against existing risk detection frameworks.
• Analyse complex datasets, investigate anomalies and assess data quality to support reliable model development.
• Maintain clear documentation of methodologies, model changes, analytical findings and recommendations.
• Collaborate with business stakeholders, data scientists and engineers to implement model enhancements and communicate findings.

Requirements & Qualifications

• Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related discipline.
• 3–5 years of relevant experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics.
• Strong hands-on proficiency in Python and SQL, including data extraction, transformation and exploratory analysis.
• Experience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models.
• Familiarity with feature engineering, back-testing, threshold calibration and model performance evaluation, including precision and recall.
• Ability to translate business or operational requirements into analytical specifications, model logic and measurable risk indicators.
• Experience working with large datasets, data quality assessment and analytical documentation.
• Strong analytical, problem-solving and communication skills, with the ability to explain technical findings to non-technical stakeholders.

Preferred Skills

• Experience with model monitoring, data drift, concept drift and delayed or incomplete outcome labels.
• Experience building dashboards using Tableau or similar visualisation tools.
• Familiarity with CI/CD, MLOps, Spark/PySpark, AWS Redshift or AWS Glue.
• Knowledge of network or graph analytics for identifying related entities and fraud patterns.
• Experience with claims, grants, workforce, training or regulatory datasets.
• Familiarity with Singapore public-sector projects and government data-classification requirements.

Interested candidates are invited to apply via the “Apply Now” button.

We regret that only shortlisted candidates will be notified.

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Nexbridge Recruitment Pte Ltd|26C3616

EA Personnel: Guan Jiayi|R22109847