Hybrid Senior Business Analyst – Optimisation (Pairings & Crew Scheduling) bei Scoot
Scoot · Singapore, Singapur · Hybrid
- Senior
- Optionales Büro in Singapore
Summary
As a Senior Business Analyst – Optimisation, you will be responsible for designing, developing, and enhancing optimisation models that drive the generation of cost-efficient, regulatory-compliant, and crew-friendly flight pairings and schedules. You will work closely with stakeholders across Crew Planning, IT, Operations, and vendor partners to translate business needs into mathematical models and actionable solutions.You will lead initiatives that influence strategic planning, operational execution, and crew satisfaction by optimising pairing construction and roster generation using advanced analytics, machine learning, and mathematical optimisation techniques.
Job Description
Key Responsibilities:
Design, write, and maintain mathematical optimisation models for pairing and crew schedule generation.
Lead end-to-end development and deployment of optimisers, including modelling, algorithm design, parameter tuning, and validation.
Collaborate with Crew Planning, Rostering, Flight Operations, and IT teams to ensure that optimisation outputs align with business rules, regulatory requirements, and labour agreements.
Analyse crew utilisation, trip coverage, reserve usage, and stability to identify areas for further optimisation.
Work with software vendors (e.g., AIMS) to enhance or integrate optimisation capabilities into existing systems.
Continuously refine models based on operational feedback, data trends, and crew satisfaction metrics.
Provide technical leadership and mentorship within the optimisation team and across related projects.
Present findings and optimisation recommendations to senior leadership and cross-functional stakeholders.
Contribute to strategic roadmaps and innovation in digital crew enablement initiatives.
Required Qualifications:
PhD or MSc in Mathematics, Operations Research, Computer Science, or related field with specialisation in Optimisation.
Minimum 8+ years of hands-on experience in developing and deploying optimisation models, preferably in the aviation, transport, or logistics domain.
Strong understanding of crew pairing, rostering, and fatigue management regulations.
Proficient in linear/integer programming, heuristic/metaheuristic methods, and solver technologies (e.g., CPLEX, Gurobi).
Experience with modern programming languages such as Python, C++, or Java.
Familiarity with airline scheduling software suites and crew management systems (AIMS, Jeppesen, etc.) is highly desirable.
Demonstrated ability to lead cross-functional projects and influence without authority.
Excellent communication skills – capable of explaining complex models to both technical and non-technical audiences.
Preferred Attributes:
Prior experience in airline operations or airline crew planning environment.
Exposure to machine learning techniques used in predictive crew behaviour modelling or disruption recovery.
Proven record of academic or industry publications in optimisation or scheduling.
