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Company Overview
A leading Commercial Aerospace organization, this company is a world-class Original Equipment Manufacturer (OEM) and Maintenance, Repair, and Overhaul (MRO) service provider. With 50 years of proven aviation expertise, the organization delivers end-to-end solutions across aircraft life cycles, supported by skilled engineers and technicians across Asia Pacific, the U.S., and Europe. Their mission is to maintain safe, efficient, and innovative aerospace operations globally.
Role Overview
The Principal Data Scientist will deliver practical analytics and AI solutions for operational and engineering use cases. This role focuses on advanced data analytics, machine learning, optimisation, statistical modelling, and emerging Generative AI (GenAI) and agentic approaches to address complex problems and create measurable business impact.
This is an individual contributor role, providing exposure to enterprise-scale data platforms and cloud-governed environments. The role collaborates closely with business stakeholders to understand operational needs and technical teams to design and deploy production-ready solutions that support informed decision-making.
Key Responsibilities
Develop and apply statistical models, machine learning, and advanced analytics to solve business challenges
Conduct data exploration, feature engineering, model development, and validation
Translate business problems into structured analytical solutions and actionable insights
Communicate findings through visualizations, presentations, and data storytelling
Collaborate with data engineers and software engineers to deploy and operationalize analytics solutions
Maintain adherence to data quality, governance, and documentation standards
Stay updated on industry trends and advancements in data science, AI, and analytics methodologies
Required Qualifications & Experience
Degree, Master’s, or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline
Extensive experience in data analytics or data science roles, preferably in aerospace, engineering, or asset-intensive environments
Strong foundation in statistics, probability, and data analysis
Proficiency in Python, SQL, and relevant data libraries and frameworks
Experience with machine learning, forecasting, optimisation, or decision science techniques
Experience working with structured and/or unstructured datasets
Demonstrated ability to manage multiple projects in fast-paced environments
Strong analytical and problem-solving skills with a passion for complex datasets
Preferred/Advantageous Skills & Experience
Experience or working knowledge in Operations Research (OR), optimisation, scheduling, or resource allocation
Exposure to cloud-based analytics platforms (e.g., AWS)
Familiarity with CI/CD concepts and version control (e.g., Git)
Soft Skills & Attributes
Strong analytical and problem-solving capabilities
Ownership and accountability for deliverables
Detail-oriented with a focus on data quality, security, and reliability
Clear communication skills for both technical and non-technical audiences
Comfortable in project-based, fast-paced environments
Ability to work independently while collaborating effectively with cross-functional teams
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.
1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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