Title:  Principal Data Scientist

Business Area: Commercial Aerospace

Work Location: 600 West Camp Road

About Commercial Aerospace

ST Engineering’s Commercial Aerospace business is a world-class Original Equipment Manufacturer (OEM) and Maintenance, Repair and Overhaul (MRO) service provider with proven solutions for practically every stage of an aircraft life cycle. With 50 years of reputable track record in aviation, backed by a highly experienced team of engineers and technicians across facilities in Asia Pacific, the U.S. and Europe, we know what it takes to keep the world flying safely.

About the role

Role Overview

We are seeking an Assistant / Principal Data Scientist to join Commercial Aerospace, delivering practical, real‑world analytics and AI solutions for operational and engineering use cases. The role focuses on applying advanced data analytics, machine learning, optimisation, statistical modelling, and emerging Generative AI (GenAI) and agentic approaches to solve complex problems and deliver measurable impact.

This is an individual contributor role with exposure to enterprise‑scale data platforms and cloud‑governed environments, working closely with both business stakeholders to understand operational needs and technical teams to design and deliver production‑ready solutions that support informed decision‑making.

Key Responsibilities

• Develop and apply statistical models, machine learning, and advanced analytics to address business challenges.
• Perform data exploration, feature engineering, model development, and validation.
• Translate business problems into structured analytical solutions and actionable insights.
• Communicate findings clearly through visualisations, presentations, and data storytelling.
• Collaborate with data engineers and software engineers to deploy and operationalise analytics solutions.
• Adhere to data quality, governance, and documentation standards.
• Stay abreast of industry trends and advancements in data science to enhance technical knowledge and apply the latest methodologies.

Required Qualifications & Experience

The ideal candidate will possess a strong background in a quantitative field such as Data Science, Statistics, Computer Science, or a related discipline, complemented by extensive experience in a data analytics or data science role, preferably within an aerospace or engineering context.

• Degree, Masters or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline.
• Demonstrated ability to manage multiple projects simultaneously and deliver results in a fast-paced environment.
• Strong problem-solving skills and a passion for unraveling complex datasets.
• Strong foundation in statistics, probability, and data analysis.
• Proficient in programming languages such as Python, or SQL, along with experience in data libraries and frameworks.
• Experience with machine learning, forecasting, optimisation, or decision science techniques.
• Experience working with structured and/or unstructured datasets.

Preferred/Advantageous Skills & Experience

• Experience or working knowledge in Operations Research (OR), particularly in optimisation, scheduling, or resource allocation, will be advantageous.
• Exposure to cloud‑based analytics platforms (e.g. AWS).
• Prior experience in engineering, manufacturing, aerospace, or asset‑intensive environments is an advantage.
• Familiarity with CI/CD concepts and version control (e.g. Git).

Soft Skills & Attributes

• Strong analytical and problem‑solving skills.
• Strong sense of ownership and accountability.
• Detail‑oriented with a strong focus on reliability, data quality, and security.
• Clear communicator who can explain technical concepts to non‑technical stakeholders.
• Comfortable working in a project‑based, fast‑paced environment.
• Able to work independently while collaborating effectively across teams.