Data Scientist (1 year contract)

Visa Hunt; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Yokogawa Singapore seeks a hands-on AI researcher/engineer to develop LLM, Generative AI, and Agentic AI solutions for chemical and process industries. You will design AI-powered apps using plant data, engineering knowledge, and maintenance records to improve decision making.

The role covers RAG systems, knowledge graphs, semantic search, and intelligent agents that integrate with enterprise systems, digital twins, and engineering tools to automate workflows and support operations.

Qualifications

• Masters/Degree in Engineering/Sciences
• 3-6 years of relevant experience
• Experience with knowledge graphs, semantic search, industrial digital twins, or engineering knowledge management systems.
• Experience applying AI to plant operations, sustainability, energy optimization, asset performance management, or process safety use cases.
• Familiarity with Responsible AI, AI governance, cybersecurity, and human-in-the-loop decision-support systems.
• Experience in real-world data science projects, internships, hackathons, and personal projects
• Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn
• Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI
• Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval

Responsibilities

• Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications
• Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making
• Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights
• Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations
• Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments
• Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance
• Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
• Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
• Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management
• Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization

Skills

Knowledge graphs

Semantic search

Industrial digital twins

Engineering knowledge management

Plant operations AI

Sustainability

AI governance

Cybersecurity

Human-in-the-loop

Python

Pandas

NumPy

Scikit-learn

Matplotlib

Seaborn

APIs

Flask

Django

FastAPI

PostgreSQL

MinIO

SQL

Education

Master's degree in Engineering/Sciences

Tools

Flask

Django

FastAPI

PostgreSQL

MinIO

Job description

Job Description

• Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications
• Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making
• Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights
• Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations
• Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments
• Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance
• Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
• Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
• Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management
• Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization

Job Requirements

• Masters/Degree in Engineering/Sciences
• 3-6 years of relevant experience
• Experience with knowledge graphs, semantic search, industrial digital twins, or engineering knowledge management systems.
• Experience applying AI to plant operations, sustainability, energy optimization, asset performance management, or process safety use cases.
• Familiarity with Responsible AI, AI governance,cybersecurity, and human-in-the-loop decision-support systems.
• Experience in real-world data science projects, internships, hackathons, and personal projects
• Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn
• Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI
• Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval

Yokogawa is an Equal Opportunity Employer.Yokogawa wants a diverse, equitable and inclusive culture.We willactively recruit, develop, and promote people from a variety of backgrounds whodiffer in terms of experience, knowledge, thinking styles, perspective,cultural background, and socioeconomic status.We will notdiscriminate based on race, skin color, age, sex, gender identity andexpression, sexual orientation, religion, belief, political opinion,nationality, ethnicity, place of origin, disability, family relations or anyother circumstances. Yokogawa values differences and enables everyone tobelong, contribute, succeed, and demonstrate their full potential.