Data Scientist - Supply Chain Optimisation

CBSbutler Holdings Limited trading as CBSbutler
Hounslow, TW3 1DA, United Kingdom
Last month
Applications closed

Related Jobs

View all jobs

Data Scientist

Adaptable Recruitment Liverpool, United Kingdom
£50,000 – £60,000 pa Hybrid

Data Scientist

Harnham - Data & Analytics Recruitment London, United Kingdom
£50,000 – £65,000 pa Hybrid

Data Scientist

Searchability NS&D Cheltenham, United Kingdom
£45,000 – £75,000 pa Permanent Clearance Required

Data Scientist

Franklin Bates London, United Kingdom
£55,000 – £65,000 pa Hybrid

Data Scientist

Hays Technology London, United Kingdom
£600 – £1,000 pd

Data Scientist

ISR Recruitment Exeter, Devon, United Kingdom
£50,000 – £60,000 pa Hybrid
Posted
10 Mar 2026 (Last month)

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

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.