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Data Scientist (Healthcare)

lead5,500 SGD · period not specifiedSingapore, SGScore 72.5/1004d ago
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📊 AI / ML / Data Science: salaries and demand on the market
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ValidationDesignGenerative AI Application Development and DeploymentAI AgentsSecurityDevelopmentData PipelineGitHub repositoryClinical Data ManagementData Quality AssuranceMLOpsEngaging Stakeholders
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Description
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
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