Production Data Scientist: ML, Anomaly & Risk Modeling

RAPSYS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE. LTD. invites applications for a data science specialist focused on turning large operational datasets into actionable insights. You will prototype and productionize machine-learning models, perform feature engineering, and collaborate with engineers and domain experts.

The role emphasizes building scalable data pipelines, ensuring data quality, and integrating analytics into real-world workflows. Strong Python/SQL skills and experience with model evaluation are essential.

Qualifications

• Degree in data science, CS, statistics or ML; data analytics preferred.
• Experience with large, messy datasets and applied data science incl. feature engineering and model evaluation.

Responsibilities

• Analyze large operational datasets to identify patterns, anomalies, outliers, and risk indicators.
• Develop approaches for anomaly detection, clustering, segmentation, and risk scoring.
• Build supervised machine-learning models with historical labels where available.
• Perform feature engineering using structured and unstructured data.
• Design evaluation methods for model performance including precision and recall.
• Collaborate with domain experts to integrate analytical outputs into workflows.
• Build and maintain data-processing pipelines to support scalable modelling.
• Develop production-ready model and scoring pipelines integrated with apps.
• Monitor model performance, data quality and drift post deployment.
• Explore opportunities for workflow redesign and automation.
• Support use of LLMs and other AI techniques alongside traditional methods.
• Develop reusable analytical components for multiple agency engagements.

Skills

Python

SQL

Analytical problem solving

Model evaluation

Education

Degree in Data Science, Computer Science, Statistics, Machine Learning

Tools

Git

APIs

CI/CD

Job description

RAPSYS TECHNOLOGIES PTE. LTD. invites applications for a data science specialist focused on turning large operational datasets into actionable insights. You will prototype and productionize machine-learning models, perform feature engineering, and collaborate with engineers and domain experts.

The role emphasizes building scalable data pipelines, ensuring data quality, and integrating analytics into real-world workflows. Strong Python/SQL skills and experience with model evaluation are essential.