About Data Analytics, GEC

The Group Engineering Centre (GEC) is a centralized core function within ST Engineering (Singapore Technologies Engineering), established to drive technological and operational excellence across the entire multinational group. Within the Group Engineering Centre (GEC), the data analytics function primarily operates through the Data Analytics Strategic Engineering Centre (DA SEC). 

Its core role is to serve as a centralized hub that deepens and scales advanced data capabilities across the entire global organization. Rather than working for just one department, the team develops cross-functional intelligence, building models and platforms that serve both internal business clusters and external commercial or defence clients.

About The Role

Work Location: 600 West Camp Road

We are seeking a Senior AI/ML Engineer to develop machine learning and GenAI solutions that enhance operational performance, asset reliability, and business outcomes. Working alongside engineering and operations teams, you will help transform data into scalable products and actionable insights.

Key Responsibilities

Data Science & Analytics

• Gather, process, and analyse data from multiple sources to uncover insights and opportunities.
• Develop statistical, machine learning, and AI models to address business and operational challenges.
• Perform exploratory data analysis, feature engineering, model training, and evaluation.
• Design and implement analytical solutions that support decision-making and operational improvements.
• Develop dashboards, visualisations, and reports for stakeholders.

Product & Solution Development

• Contribute to the development of analytics products and AI-enabled solutions.
• Work closely with users and stakeholders to understand requirements and translate them into practical data products.
• Continuously improve existing models, products, and processes based on feedback and changing business needs.
• Deliver solutions that balance business value, technical quality, and speed of execution.

AI & Emerging Technologies

• Leverage AI assistants, copilots, and agentic AI tools to enhance productivity and accelerate development.
• Explore and evaluate new technologies, methodologies, and tools that improve solution effectiveness.
• Apply automation and intelligent workflows where appropriate.

Engineering & DevOps

• Write clean, maintainable, and well-documented code.
• Use Git and version control best practices for collaborative development.
• Support deployment, monitoring, testing, and maintenance of analytics solutions.
• Contribute within an Agile and DevOps-oriented delivery environment.

Professional Qualifications and Skills

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Analytics, or a related quantitative discipline.
• Minimum 5 years of relevant process engineering experience, with demonstrated success in leading process improvement initiatives, operational optimisation projects, and cross-functional teams.
• Strong foundation in python programming, SQL and data querying, statistics and probability, machine learning fundamentals, data structures and algorithms, data preparation and feature engineering
• Familiarity with data science and analytics tools such as Pandas, NumPy, Scikit-learn, Power BI, Tableau, or equivalent technologies.
• Familiarity with software engineering best practices, including version control (Git), testing, documentation, and collaborative development workflows.
• Exposure to Agile, DevOps, MLOps, CI/CD, or modern software delivery practices is advantageous.
• Exposure to cloud and modern data platforms such as Azure, AWS, GCP, Databricks, Microsoft Fabric, or similar technologies is advantageous.
• Experience or exposure in predictive maintenance, condition-based monitoring, anomaly detection, asset health analytics, reliability engineering, time-series analytics, or Industrial IoT applications will be an advantage.
• Familiarity with graph-based analytics, causal inference, knowledge graphs, root cause analysis, or graph databases (e.g. Neo4j) is a plus.
• Passion for leveraging AI technologies, including Generative AI, Large Language Models (LLMs), AI agents, and intelligent automation to solve business problems.
• Self-motivated and proactive learner with the ability to independently research, troubleshoot, and acquire new skills in a rapidly evolving technology landscape.
• Strong problem-solving and analytical thinking skills, with the ability to translate business challenges into practical, scalable solutions.
• Effective communicator and team player who can collaborate with engineers, operations personnel, data professionals, and business stakeholders.
• Able to thrive in a fast-paced, product-oriented environment where rapid experimentation, continuous improvement, and delivery of impactful solutions are expected.

What We Offer

At ST Engineering, we are committed to fostering an inclusive and engaging workplace where innovation thrives and careers flourish. As part of our team, you will benefit from:

• Opportunities for continuous professional development and career advancement.
• Exposure to cutting-edge technologies and projects with global impact.
• A collaborative environment that values diversity, creativity, and forward thinking.
• Competitive remuneration package and comprehensive benefits.
• A supportive work culture that encourages work-life balance and wellbeing.

How to Apply

We welcome applications from fresh grads and talented individuals who are passionate about data analytics and eager to contribute to meaningful projects that make a difference. Join us at ST Engineering Hub and be a part of our transformative journey.