- Location
- Singapore HQ
- Type
- Full-time
- Seniority
- Senior
- Experience
- 8+ years
- Education
- PhD
- Source
- Workday
Description
Summary
As a Senior Business Analyst – Optimisation, you will lead the design, development, and enhancement of optimisation solutions across the airline’s Operations Research portfolio. Expanding beyond pairings and crew scheduling, you will drive initiatives that improve crew and aircraft utilisation, network and schedule robustness, disruption recovery, resource planning, and overall profitability.You will work closely with stakeholders across Crew Planning, OCC, Network Planning, Maintenance/Engineering, Flight Operations, and vendor partners to translate business needs, regulations, and labour agreements into mathematical models and operationally actionable solutions. You will influence strategic planning, day-of-operations decision-making, and crew satisfaction through optimisation, advanced analytics, and machine learning-enabled decision support.
Job Description
Responsibilities
Design, write, and maintain mathematical optimisation models and decision-support tools for:
Crew: pairing construction, roster generation, reserve planning, training integration, accommodation/transport cost optimisation
Fleet/Aircraft: tail assignment/aircraft routing, maintenance-integration, aircraft swaps
Network/Schedule: schedule feasibility and robustness, turn times, curfew/airport constraints, block time standards
Disruption Management: recovery optimisation for aircraft and crew, with passenger reaccommodation interfaces
Resource Planning: manpower forecasting/base sizing, ground resource/gate assignment (as applicable)
Lead end-to-end development and deployment of optimisers, including modelling, algorithm design, parameter tuning, validation, and operationalisation. Define functional/non-functional requirements, manage backlogs, and run UAT with end users.
Collaborate with Crew Planning, Rostering, Flight Operations, OCC, Network Planning, Maintenance/Engineering, Ground Operations, Finance, Revenue Management, and IT teams to ensure optimisation outputs align with business rules, regulatory requirements, airport/airspace constraints, maintenance plans, labour agreements, and safety standards.
Analyse crew and aircraft utilisation, robustness, and cost drivers (e.g., block hours per tail/FTE, reserve coverage, deadhead/hotel/transport, OTP, completion factor, reactionary delay) to prioritise and refine optimisation opportunities.
Work with software vendors to enhance or integrate optimisation capabilities into existing systems; evaluate build vs buy options, support RFPs, and manage vendor deliverables.
Continuously refine models based on operational feedback, data trends, and crew/operations satisfaction metrics; ensure model explainability and auditable constraints.
Establish governance and versioning for business rules, parameters, and constraint changes; maintain data quality standards and SLAs with data providers.
Define KPIs and benefits frameworks; run experiments (backtests, A/B tests, shadow runs) to validate value vs baseline and ensure benefits realisation with Finance.
Provide technical leadership and mentorship within the optimisation team and across related projects; contribute to strategic roadmaps and innovation in digital operations and crew enablement.
Present findings, scenarios, and optimisation recommendations to senior leadership and cross-functional stakeholders; drive adoption through training, playbooks, and change management.
Qualifications
PhD or MSc in Mathematics, Operations Research, Computer Science, or related field with specialisation in Optimisation.
Minimum 8+ years of hands-on experience developing and deploying optimisation models, preferably in aviation, transport, or logistics, with demonstrable outcomes across crew, fleet/aircraft routing, schedule design, or disruption recovery.
Strong understanding of crew pairing, rostering, and fatigue management regulations, plus working knowledge of aircraft/maintenance integration, tail assignment, and day-of-operations decision-making.
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; exposure to OCC tools and tail assignment/recovery systems is a plus.
Demonstrated ability to lead cross-functional projects and influence without authority in operational and unionised environments, Agile delivery experience.
Excellent communication skills – capable of explaining complex models, trade-offs, and solver outcomes to both technical and non-technical audiences; strong stakeholder and change management skills.
Preferred Attributes
Prior experience in airline operations (Crew Planning, OCC, Network, or Maintenance/Engineering).
Exposure to machine learning for demand/absence forecasting, delay propagation, disruption recovery, or maintenance reliability.
Experience measuring value realisation (cost savings, utilisation gains, robustness improvements) via experiments and operational pilots.
Vendor and RFP experience for optimisation platforms and integrations; cloud/data platform familiarity.
