Job Description
Job overview and responsibility
- Build and lead a high-performing advanced analytics capability spanning operations research, machine learning, and applied AI, with responsibility for team structure, hiring, onboarding, coaching, and technical standards. - Define and enforce the team’s engineering and scientific delivery practices, including coding conventions, peer review, model documentation, experiment tracking, evaluation discipline, and clear definitions of done for algorithm deliverables. - Own end-to-end algorithm delivery for applied AI and optimisation use cases, translating ambiguous business problems into well-formulated solutions with measurable outcomes and agreed success criteria. - Take a hands-on leadership role in early engagements by shaping models, writing or reviewing code, validating outputs, and setting the technical benchmark for future delivery teams. - Partner with business stakeholders, product teams, and engineering leads to scope use cases, confirm data readiness, assess feasibility, estimate algorithm effort, and align delivery plans with operational priorities. - Support strategic pre-sales and solutioning activities by shaping technically credible, commercially compelling AI and optimisation solutions for complex operational environments. - Present complex modelling approaches, technical trade-offs, delivery risks, and business value clearly to client operations, engineering, and leadership stakeholders. - Coordinate cross-entity delivery with offshore and distributed teams by defining component boundaries, data requirements, handover points, governance expectations, and quality controls for each engagement.
Required skills and experiences
- Master’s or PhD degree in Operations Research, Computer Science, Applied Mathematics, Statistics, Machine Learning, Artificial Intelligence, or a closely related quantitative discipline.
- 10+ years of experience building machine learning, optimisation, or advanced algorithmic systems, including at least 3 years leading technical teams with hiring, coaching, and delivery accountability.
- Proven track record delivering algorithmic solutions into production within complex operational domains such as aviation, aerospace, manufacturing, logistics, mobility, or other mission-critical environments.
- Recent hands-on proficiency in Python, with production experience in optimisation solvers such as Gurobi, CPLEX, COPT, or OR-Tools, and/or modern ML frameworks such as PyTorch, scikit- learn, or equivalent technologies.
- Strong ability to translate business and operational challenges into mathematically sound formulations, measurable objectives, and practical implementation plans.
- Demonstrated leadership in technical governance, including model review, code quality, experiment tracking, production readiness, documentation, and delivery risk management.
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- Excellent English communication skills, with the ability to engage confidently with senior stakeholders, client teams, engineers, data scientists, and cross-border delivery teams.
Preferred skills and experiences
- Domain expertise in airline, airport, MRO, aircraft OEM, or large-scale industrial operations, particularly in areas such as maintenance scheduling, revenue management, fleet assignment, crew or resource optimisation, production planning, or asset utilisation.
- Experience building a new technical function or specialist capability from the ground up, whether in a startup, new subsidiary, new site, or transformation environment within an established organisation.
- Experience operating in multinational, cross-border, or distributed delivery models with clear data boundaries, governance controls, stakeholder alignment, and handover responsibilities.
- Personal delivery experience across both operations research and machine learning, with the ability to bridge mathematical modelling, data-driven methods, engineering implementation, and business adoption.
- Recognised contribution to the algorithm, optimisation, or applied AI community through publications, conference participation, open-source work, industry research, competitions, or equivalent technical achievements.
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Why Candidate should apply this position
- Direct interface with senior leadership in Singapore.
- A defined career development pathway within a global organization operating across aerospace, smart city, marine, and digital systems.
- Competitive total compensation package
Report to
Head of Software Services
Interview process
Interview with Senior Manager -> Interview with General Manager/C-level
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