Data Scientist (Healthcare)

GMP RECRUITMENT SERVICES (S) PTE LTD; Singapore; Sur place; SGD 120 000 - 180 000; Plein temps

Résumé du poste

GMP Recruitment Services (S) PTE LTD is hiring for a data science role focused on LLM-based and agentic AI solutions across clinical and operational challenges in Singapore. The role entails building automated data pipelines, RAG systems, and NLP-driven data analysis to extract actionable healthcare insights.

You will collaborate with cross-functional teams to integrate AI into existing clinical platforms, monitor performance, and ensure compliance with PDPA/HBRA and privacy practices.

Qualifications

• Minimum 2 years of experience in data science or a related field, preferably within a healthcare environment.
• Proven experience developing and deploying production-grade LLM and agentic AI applications, supported by a GitHub portfolio or documented project case studies.
• Strong programming skills in Python, R, and/or SQL, with experience integrating AI/ML models, LLM APIs, and cloud platforms (especially AWS).
• Solid understanding of CI/CD, MLOps, and DevSecOps practices for AI application development and deployment.
• Strong analytical, problem-solving, and communication skills, with the ability to translate clinical and operational needs into practical AI solutions.

Responsabilités

• Lead the research, design, development, and deployment of LLM-based and agentic AI solutions to address clinical and operational challenges.
• Build and maintain automated data pipelines, prompt engineering workflows, and retrieval-augmented generation (RAG) systems for AI applications.
• Develop LLM-powered applications for clinical decision support, care pathway optimisation, automated documentation, and clinical research initiatives.
• Apply NLP techniques to clean, preprocess, validate, and analyse healthcare data, ensuring high data quality and extracting actionable insights.
• Collaborate with cross-functional teams to integrate AI solutions into existing clinical platforms and data infrastructure.
• Monitor application performance, develop explainability frameworks, create reports and visualisations, and communicate findings to technical and non-technical stakeholders.
• Ensure compliance with healthcare data governance, security, privacy regulations (e.g., PDPA, HBRA), and ethical AI implementation, including data anonymisation and access management.

Connaissances

Python

R

SQL

LLM APIs

AWS

NLP techniques

GitHub portfolio

CI/CD

MLOps

DevSecOps

Outils

GitHub

AWS

Description du poste

Responsibilities

• Lead the research, design, development, and deployment of LLM-based and agentic AI solutions to address clinical and operational challenges.
• Build and maintain automated data pipelines, prompt engineering workflows, and retrieval-augmented generation (RAG) systems for AI applications.
• Develop LLM-powered applications for clinical decision support, care pathway optimisation, automated documentation, and clinical research initiatives.
• Apply NLP techniques to clean, preprocess, validate, and analyse healthcare data, ensuring high data quality and extracting actionable insights.
• Collaborate with cross-functional teams to integrate AI solutions into existing clinical platforms and data infrastructure.
• Monitor application performance, develop explainability frameworks, create reports and visualisations, and communicate findings to technical and non-technical stakeholders.
• Ensure compliance with healthcare data governance, security, privacy regulations (e.g., PDPA, HBRA), and ethical AI implementation, including data anonymisation and access management.

Requirements

• Minimum 2 years of experience in data science or a related field, preferably within a healthcare environment.
• Proven experience developing and deploying production-grade LLM and agentic AI applications, supported by a GitHub portfolio or documented project case studies.
• Strong programming skills in Python, R, and/or SQL, with experience integrating AI/ML models, LLM APIs, and cloud platforms (especially AWS).
• Solid understanding of CI/CD, MLOps, and DevSecOps practices for AI application development and deployment.
• Strong analytical, problem-solving, and communication skills, with the ability to translate clinical and operational needs into practical AI solutions.

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