Data Scientist
Data Scientist/ Optimisation Engineer
London - Onsite 2/3 days a week
6 month contract
Inside of IR35
£575 per day via Umbrella
We’re looking for an Operational Research–focused Data Specialist to join a high-impact decision intelligence team building optimisation and decision-support products used in live operations every day
.This role is less about pure algorithmic data science and much more about applying Operational Research, optimisation, and analytical modelling to complex, real-world problems at scale. If you enjoy turning messy operational challenges into mathematically grounded, production-ready solutions, this role is for you
.You might currently work in environments such as consulting (e.g. BCG X, Oliver Wyman, Bain, McKinsey) or product-led organisations in travel, logistics, marketplaces, fintech, or platforms (e.g. airlines, delivery networks, booking platforms)
.
What you’ll
- doDesign and implement optimisation and decision-support models to improve large-scale operational outcomes (e.g. planning, scheduling, allocation, routing, capacity, trade-offs
- ).Apply Operational Research techniques such a
- s:Linear & mixed-integer programmi
- ngNetwork optimisati
- onHeuristics & approximation metho
- dsWork closely with software engineers and product teams to industrialise models into robust, scalable tools used in day-to-day operation
- s.Build production-grade Python code, including clean abstractions, testing, and performance-aware implementation
- s.Develop and maintain data pipelines to support optimisation and analytical workflow
- s.Deploy models using modern cloud and orchestration frameworks, following CI/CD best practice
s.
Core skills & experie
- nceStrong grounding in Operational Research / Optimisation, rather than purely statistical or ML-heavy data scien
- ce.Hands-on experience with mathematical optimisation (e.g. LP, MILP, heuristic
- s).Proficiency in Python for analytical and optimisation modelli
- ng.Experience translating ambiguous, real-world operational problems into structured analytical mode
- ls.Ability to balance solution quality, runtime, robustness, and real-world constrain
ts.Technical toolkit (experience with some of the followi
- ng)Optimisation solvers (e.g. Gurobi, CPLEX, OR-Too
- ls)Python libraries (e.g. pandas, numpy, optimisation framewor
- ks)SQL and data engineering fundament
- alsCloud environments (AWS or simil
- ar)Version control (Git), testing, CI
- /CDOrchestration tools (e.g. Airflow, Dagst