Hiring nowSupply chain, logistics and mobility analytics

Logistics Optimisation Engineer

Also called Logistics AI Engineer

A Logistics Optimisation Engineer turns routing, scheduling and allocation problems into models that produce workable plans. They cut cost and improve service without breaking the real constraints of the operation.

What they do

They take a messy operational problem, such as vehicle routes, shift patterns or warehouse allocation, and turn it into a model with clear constraints and an objective. They build the data pipelines that feed it, add demand or travel-time forecasts where needed, and run the solver. Then they test the plan against how the operation really runs. They compare it with current practice, explain the trade-offs to planners, and adjust when drivers, depots or customers push back. They also monitor results once plans go live.

What a strong hire delivers

Within the first months, a strong hire delivers a feasible plan for one real operational problem, with a clear comparison against what the business does today. They set up reliable data inputs and agree with planners which constraints are hard and which are soft. They leave behind a model the team can rerun, explain and improve, and a clear view of where the next gains sit.

How you can tell they are good

Ask them to walk through a plan they built that went live. Strong people explain how they chose constraints, what they simplified, and what changed after planners saw the output. They compare results against a sensible baseline and are honest about where the model fell short. Be wary of anyone who talks only about solver choice or shows gains that ignore operational limits.

Why it is hard to fill

The title is used loosely, so candidates vary widely. Many people know operations research theory but have never shipped a plan that dispatchers trust. Others know logistics systems but not solvers. The strongest sit across both, plus data engineering and forecasting. That mix is rare, and the best are usually embedded in operations teams, not visibly on the market.

Where to find them

Look to operations research teams, supply-chain analytics groups and transport planning functions. Typical employers are carriers, retailers, third-party logistics providers, delivery platforms and routing software firms. Useful titles include operations research analyst, optimisation scientist, supply-chain data scientist and transport engineer. Some come from academic optimisation groups, though check they have worked with live operational data.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Logistics Optimisation Engineer

  1. Describe a routing or scheduling problem you modelled. What were the hard constraints, and how did you find them?

    Strong answers show they worked with planners and drivers to separate hard rules from preferences. They name specific constraints and how they validated them. Worry if constraints came only from a spec or if they cannot say what was relaxed.

  2. Your solver returns a plan that planners reject. What do you do?

    Good candidates treat rejection as information. They ask why, check for missing constraints, and adjust the model or explain trade-offs. Worry if they defend the maths or blame users without investigating.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are looking for a Logistics Optimisation Engineer to improve how we plan routes, schedules and resource use. You will turn real operational problems into models that produce feasible plans, and work closely with the people who run them. Your work will be judged on gains that hold up in practice.

What you will do

  • Model routing, scheduling and allocation problems with clear constraints and objectives
  • Build and maintain the data pipelines that feed planning models
  • Develop demand and travel-time forecasts to support planning
  • Compare proposed plans with current operations and report results clearly
  • Work with planners and operations staff to refine constraints and handle exceptions
  • Monitor live plans and improve models based on outcomes

What you will bring

  • Shipped at least one routing or scheduling model used in a real operation
  • Strong grounding in optimisation and operations research methods
  • Practical experience with solver libraries and routing engines
  • Solid probability, statistics and time-series modelling skills
  • Able to build and maintain reliable data pipelines
  • Clear communicator with non-technical operational teams

Nice to have

  • Experience with warehouse or fleet management systems
  • Experience with re-planning under disruption
  • Background in transport engineering or supply-chain analytics

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Optimisation and operations researchAdvancedChoose actions subject to objectives and constraints
  • Time-series modellingAdvancedModel temporal dependencies and forecasts
  • Data pipelinesWorkingBuild reliable ingestion and transformation systems
  • Probability and statisticsWorkingQuantify variability and statistical evidence

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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