Manufacturing Data Scientist

Halewood
5 days ago
Create job alert

Manufacturing Data Scientist

Salary: £46,587.88 (inclusive of 35% holiday bonus for 33 days per year; 25 vacation & 8 bank holidays)

Contract: Permanent

Hours: Monday to Thursday: 07:00 - 15:30, Friday: 07:00 - 12:30

As a Manufacturing Data Scientist, you will play a key role in shaping how data is used to improve efficiency, quality, throughput, and sustainability across the plant.

You will design, develop, and maintain a portfolio of data-driven products and projects that turn complex manufacturing data into clear, actionable insights for operators, engineers, and leadership. You will work as part of the plant manufacturing team while also being embedded within Ford's wider global data science and analytics community, helping to scale successful solutions across the enterprise.

This role embodies Ford's commitment to continuous improvement and data-led decision-making, enabling teams to adapt and improve based on the insights you deliver.

Essential

Degree-level education in a relevant subject (such as Mathematics, Statistics, Data Analytics, Computer Science, Physical Sciences) or equivalent professional experience within an engineering or automotive environment
Strong Python expertise
Experience applying machine learning techniques in real-world scenarios
Solid grounding in statistical methodologies and analysis

Desirable

SQL proficiency
Experience with cloud computing platforms

What You'll Do

Leadership & Ford+ Behaviours

Demonstrate Ford+ behaviours in your daily work: ownership, collaboration, integrity, inclusion, customer focus, and continuous learning
Lead or co-lead cross-site analytics initiatives and contribute to a shared analytics playbook

Data, Analytics & Insight

Extract, transform, analyse, and report manufacturing data from multiple sources
Put robust data quality, governance, and security controls in place
Identify process bottlenecks and key drivers of variability to improve OEE, yield, scrap, downtime, cycle times, and energy usage
Build clear dashboards and visualisations, communicating insights in accessible, non-technical language

Modelling & Deployment

Develop and deploy predictive and prescriptive models (e.g. predictive maintenance, defect forecasting, anomaly detection, capacity planning)
Operationalise models using cloud and MLOps best practices, including monitoring, documentation, retraining, and explainability

Collaboration & Change

Work closely with engineering, quality, maintenance, IT, production, and supply chain teams to translate insights into action
Support pilot projects and help scale successful solutions across sites
Contribute to analytics training and capability-building within the plant

Ethics, Safety & Governance

Ensure data privacy, security, and compliance considerations are embedded in all analytics work
Champion responsible, safe, and ethical use of data and models

Benefits

Access to our Employee Development and Assistance Programme
A unique opportunity to access Fords Privilege scheme - allowing you to purchase Ford vehicles at a discount
A great salary increasing yearly, along with our competitive pension scheme
An excellent work-life balance, including a generous holiday allowance of 25 days (inclusive of set shutdown dates)
Cycle to Work Scheme
On site facilities such as a gym, sauna and steam room

Related Jobs

View all jobs

Software Engineer

PLM Functional Consultant

PLM Business Analyst Consultant

Mechanical Design Engineer

Head of Commercial

Head of Commercial

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.

Robotics Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Robotics looks futuristic from the outside. People picture humanoid machines, cutting-edge labs & young engineers writing complex code. In the UK job market, the reality is more practical and more encouraging for career switchers: robotics is already embedded across manufacturing, logistics, healthcare, agriculture, defence, construction & inspection. That means there are real jobs for people in their 30s, 40s & 50s who bring operational experience, delivery skills, quality discipline & the ability to work with real-world systems. This article gives you a clear UK reality check on robotics careers for career switchers: what roles genuinely exist, which paths are most realistic, what skills employers actually hire for, how long retraining tends to take & whether age is a factor.

How to Write a Robotics Job Ad That Attracts the Right People

Robotics is moving rapidly from research labs into real-world deployment. Across the UK, robots are now used in manufacturing, logistics, healthcare, defence, agriculture, autonomous vehicles and service industries. As adoption accelerates, demand for skilled robotics professionals continues to grow. Yet many employers struggle to attract the right candidates. Robotics job adverts often receive either very few applications or large numbers of unsuitable ones. Experienced robotics engineers, meanwhile, routinely skip adverts that feel vague, unrealistic or disconnected from how robotics systems actually work in practice. In most cases, the problem is not the talent pool — it is the job advert itself. Robotics professionals are systems thinkers. They care deeply about constraints, integration and real-world performance. A poorly written job ad signals weak technical understanding and unrealistic expectations. A well-written one signals credibility, seriousness and a mature robotics programme. This guide explains how to write a robotics job ad that attracts the right people, improves applicant quality and positions your organisation as a credible employer in the robotics sector.

Maths for Robotics Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for robotics jobs in the UK it is easy to assume you need degree level maths across everything. Most roles do not work like that. What hiring managers usually mean by “strong maths” is much more practical: you can move confidently between coordinate frames you understand rotations without getting lost you can reason about kinematics, control, uncertainty & optimisation you can turn that maths into working code in a robotics stack This guide focuses on the only maths topics that consistently show up across common UK roles like Robotics Software Engineer, Controls Engineer, Autonomous Systems Engineer, Perception Engineer, SLAM Engineer, Robotics Research Engineer, Mechatronics Engineer & Robotics Systems Engineer. You will also get a 6 week learning plan, portfolio projects & a resources section so you can learn fast without drowning in theory.