Data Scientist - Supply Chain Optimisation

Hounslow
1 month ago
Applications closed

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Data Scientist - Optimisation & Operations Research

North West London (Hybrid, 3 days on-site) | £550 - £750 /day

The Opportunity

We're recruiting on behalf of a globally recognised organisation undergoing a major transformation in how it uses data to drive operational decisions. This is a rare chance to work on genuinely complex, high-impact decision-support software - embedding cutting-edge optimisation and machine learning directly into live operations.

You'll join a high-performing, Agile product squad as a full-stack Data Scientist, sitting at the intersection of data engineering, ML, and operations research.

What You'll Be Doing

Designing and delivering optimisation and ML models (linear/mixed-integer programming, heuristics, supervised/unsupervised learning) in Python, from prototype to production

Building robust, automated data pipelines and integrating models into cloud-based deployment pipelines with CI/CD

Owning features end-to-end - from stakeholder requirements through to algorithm hardening, edge-case handling, and value measurement

Working with orchestration frameworks (Dagster/Airflow), experiment tracking (MLflow), and containerised infrastructure (Docker/ECS)

Collaborating closely with business stakeholders and contributing to roadmap and feature prioritisation What We're Looking For

Strong operational research and optimisation background - this is a must

Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages

Production ML/optimisation software experience - you've shipped models that run at scale

Cloud platform experience (AWS preferred); familiarity with SageMaker, DVC, GitHub Actions a bonus

Strong SQL and data engineering fundamentals

Experience in airline, aviation, transport, or engineering/maintenance environments is highly desirable

Master's degree (or equivalent) in Data Science, ML, or Operational Research - or strong demonstrable industry experience

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