Senior Operations Research Engineer
A.P. Moller - Maersk (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted on 15 Sept
Reach people at A.P. Moller - Maersk
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at A.P. Moller - Maersk you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design and delivery of advanced optimization solutions for container terminal operations including equipment efficiency, yard positioning, vessel sequencing, and truck routing.
- Build operational and strategic models to improve terminal day-to-day operations and long-term planning.
- Coach junior team members and collaborate with stakeholders to embed technical solutions in production environments, measure impact, and iterate improvements.
Minimum Requirements
- 5+ years industry experience delivering optimization solutions.
- PhD or M.Sc. in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or related field (or equivalent experience).
- Proficiency in optimization modeling (LP, MILP, constraint programming, metaheuristics) and implementation in Python using solvers like PuLP, OR-Tools, Gurobi.
- Experience with stochastic optimization models evaluated against simulation; ability to translate complex operational requirements into technical solutions.
Ideal Candidate Profile
- Senior-level engineer comfortable leading technical projects from concept to delivery with mentorship experience.
- Strong operational understanding of complex resource allocation/scheduling, ideally with container terminal or similar logistics experience.
- Skilled in both optimization and simulation methods with familiarity in AI/ML approaches for operational improvements.