AI & Data Scientist – Smart Manufacturing
Agilent Technologies
- Location
- Singapore-Yishun
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 16 approvals (FY2023)
- Posted
- Sep 14, 2026
Skills
About this role
Job Description
Help build the future of intelligent manufacturing. At Agilent, we're transforming manufacturing through Artificial Intelligence, Machine Learning, Industrial IoT, and cloud-native digital platforms. We're looking for passionate AI & Data Scientists who thrive on solving complex engineering challenges and turning data into measurable business impact. As an AI & Data Scientist – Smart Manufacturing, you will develop advanced analytics, machine learning, optimization, Generative AI, and Agentic AI solutions that improve manufacturing performance across quality, productivity, equipment reliability, supply chain, engineering, and operational excellence. Working alongside software engineers, automation engineers, manufacturing engineers, solution architects, and business leaders, you'll build production-ready AI solutions that power manufacturing operations across Agilent's global network. Whether you're an early-career engineer eager to make an impact or an experienced AI professional looking to solve large-scale industrial challenges, this role offers the opportunity to shape the future of digital manufacturing. About Global OT & AI Engineering Global OT & AI Engineering builds the digital foundation that powers Agilent's global manufacturing operations. Our organization develops enterprise software, AI platforms, cloud-native applications, smart factory technologies, and enterprise data platforms that connect manufacturing sites into one intelligent ecosystem. Our mission is to transform operational data into trusted insights and intelligent decisions that improve how products are designed, manufactured, tested, and delivered worldwide. Our portfolio includes: Manufacturing AI & Advanced Analytics Global Operations Control Tower Smart Factory & Industry 4.0 Enterprise Data Platform Digital Twin Solutions Manufacturing Knowledge Platform AI-powered Decision Support Enterprise Data Exchange Platform About the Role Manufacturing operations generate vast amounts of data from production equipment, quality inspections, engineering processes, enterprise systems, and supply chain activities. Turning this data into actionable intelligence is key to improving operational performance. As an AI & Data Scientist, you will develop intelligent analytical solutions that help predict issues, optimize processes, automate decision-making, and uncover opportunities for continuous improvement. You will work across multiple business functions to translate operational challenges into scalable AI solutions that support Agilent's digital manufacturing strategy.
Key Responsibilities
Machine Learning & Advanced Analytics Develop machine learning and statistical models to improve manufacturing quality, productivity, and operational performance. Analyze manufacturing and operational data to identify trends, anomalies, and optimization opportunities. Apply predictive, classification, forecasting, and optimization techniques to solve business problems. Translate complex business requirements into data-driven solutions. AI Solution Development Design and develop AI solutions using machine learning, Generative AI, computer vision, or optimization techniques where appropriate. Prototype innovative AI applications that improve engineering and manufacturing workflows. Evaluate emerging AI technologies and recommend practical applications within manufacturing operations. Collaborate with software engineering teams to integrate AI capabilities into enterprise digital products. Production Deployment Support the deployment of AI solutions into production environments in collaboration with software and data engineering teams. Monitor model performance and continuously improve solution accuracy and reliability. Contribute to scalable AI deployment using modern cloud platforms and engineering best practices. Cross-functional Collaboration Partner with Manufacturing, Engineering, Supply Chain, Quality, and IT teams to identify opportunities where AI can