- Singapore
Working Location
Job Description
Responsibilities
position: Data Scientist
Experience Required: 7+ Years
Working Arrangement: Hybrid / Onsite (To be confirmed)
Location: Singapore
Role Summary:
We are looking for a highly skilled Data Scientist with strong expertise in Large Language Models (LLMs), prompt engineering, and AI-driven data processing solutions. The ideal candidate will have hands-on experience building intelligent workflows using Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and modern NLP techniques to process and analyze structured and unstructured data.
Key Responsibilities:
• Design, develop, and implement AI-driven solutions leveraging LLMs to process, analyze, and extract insights from structured and unstructured data/documents.
• Develop and optimize prompt engineering strategies to improve the accuracy, consistency, and reliability of LLM-generated outputs.
• Build and orchestrate intelligent AI workflows using Agentic AI frameworks for automated reasoning and data processing tasks.
• Evaluate and experiment with different LLM models, embeddings, and retrieval techniques to determine the best-fit solutions for business use cases.
• Design and implement RAG (Retrieval-Augmented Generation) pipelines integrated with vector databases and enterprise data sources.
• Ensure scalability, performance, and data quality across AI and NLP processing pipelines.
• Collaborate closely with business stakeholders, engineering teams, and data teams to deliver AI-enabled solutions aligned with business objectives.
Required Technical Skills:
• Strong hands-on experience in Python for AI development and data processing.
• Experience working with LLM APIs such as Azure OpenAI, Llama, or similar platforms.
• Practical experience in prompt engineering, prompt tuning, and LLM output evaluation.
• Hands-on experience with RAG architecture and vector databases such as FAISS, Pinecone, or Azure AI Search.
• Experience with Agentic AI frameworks such as Semantic Kernel or similar orchestration frameworks.
• Strong understanding of NLP techniques, data preprocessing, and handling large datasets.
• Familiarity with REST APIs, data pipelines, and AI model integration with enterprise applications.
• Knowledge of model evaluation, monitoring, optimization, and performance tuning techniques.
Preferred Skills:
• Experience in insurance, reinsurance, or financial services environments is an advantage.
• Exposure to enterprise AI governance and security practices.
• Experience with cloud platforms such as Azure or AWS is an advantage.
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