全职 Data Scientist 工作, 薪水 up to SGD 10,000, APAR TECHNOLOGIES PTE. LTD. Central Region (Singapore) 公司招聘中 - Ricebowl

Job Description

We are looking for a passionate Data Scientist to design, build, and deploy AI and Generative AI solutions that create measurable business impact. In this role, you will work closely with stakeholders across investment promotion, industry development, and corporate functions to develop intelligent products powered by machine learning and large language models (LLMs).

If you enjoy solving complex business problems with data, experimenting with emerging AI technologies, and building production-ready AI applications, we'd love to hear from you.

Key Responsibilities

• Partner with business stakeholders to understand priorities, identify opportunities, and translate business requirements into AI and data science solutions.
• Design, develop, and deploy machine learning and Generative AI applications that deliver measurable business value.
• Research and evaluate emerging AI technologies, including Agentic AI, Large Language Models (LLMs), predictive analytics, anomaly detection, text analytics, and customer segmentation.
• Perform data collection, preprocessing, cleaning, feature engineering, and exploratory data analysis.
• Develop, maintain, and enhance AI models and production applications, including AI assistants and chatbot solutions.
• Build backend APIs and services to support AI model deployment and system integration.
• Develop intuitive frontend interfaces and user experiences for AI-powered applications.
• Monitor, troubleshoot, and maintain deployed AI solutions to ensure reliability and performance.
• Document technical designs, implementation changes, and product enhancements.
• Identify, review, and remediate reported security vulnerabilities in AI applications and services.

Requirements

Essential Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Machine Learning, or a related discipline.
• Solid understanding of machine learning techniques for regression and classification problems.
• Proficiency in Python and commonly used data science libraries, including: pandas, matplotlib, scikit-learn XGBoost, NLTK, spaCy
• Understanding of Large Language Model (LLM) concepts, including: Context windows Embeddings Chunking Token management Retrieval-Augmented Generation (RAG)
• Experience with prompt engineering, context engineering, and prompt optimization techniques.
• Proficiency with Git and SQL.
• Experience using Business Intelligence tools such as Tableau, Qlik, Microsoft Power BI, or MicroStrategy.

EA Number: 11C4879