Manufacturing Data Scientist

Job title: Manufacturing Data Scientist

Reference: 50899

Location: Halewood, Merseyside

Duration: Permanent

Start date: ASAP

Salary: £46,587.88 pa + 33 days holiday per year; 25 vacation & 8 bank holidays

GPW Recruitment are partnering with Ford Halewood Transmissions Ltd (FHTL) in Halewood to recruit a Manufacturing Data Scientist.

Ford Halewood Transmission Limited (FHTL) develops and manufactures transmissions with an employee workforce of circa 600 people. The Plant has a proud 60-year history as a local employer and are dedicated to manufacturing high quality products. Ford are currently investing up to £230 million at the facility to transform it to build electric power units for future Ford all-electric passenger and commercial vehicles.

On Offer as the Manufacturing Data Scientist

• Salary of £46,587.88 pa
  
  
• 33 days holidays per year(25 vacation & 8 bank holidays)
  
  
• Hours of work are Monday to Thursday 7:00-15:30 and Friday 7:00-12:30
  
  Plus FHTL Employment Benefits:
  
  
• Free on-site gym facility inclusive of a sauna & steam room (outside of working hours).
  
  
• Employee assistance programmes: weekly appointments available for all employees to utilise for free such as massages, circuit classes, nutrition advise, yoga, chiropody, reiki and head massages (outside of working hours).
  
  
• An on-site physiotherapy and occupational health department is available to employees to support their health and well-being.
  
  
• Competitive pension scheme (company pays 1.5 times the amount of the employee contributions paying up to 12%)
  
  
• £750 annual attendance bonus (subject to company T&C’s).
  
  
• Access Ford's Privilege scheme - allowing you to purchase Ford vehicles at a discount
  
  
• An excellent work-life balance, including a generous holiday allowance of 25 days (inclusive of set shutdown dates)
  
  
• Cycle to Work Scheme
  
  The role
  
  A data science leader within Ford’s manufacturing ecosystem who conceptualises, develops, and maintains a portfolio of data-driven products and projects at Halewood. The role delivers measurable improvements in plant efficiency, quality, and throughput by turning complex data into actionable insights for operators, engineers, and leadership.
  
  You will contribute to a growing digital/data science community within the plant, collaborate across Ford’s central analytics network, and help scale successful solutions enterprise-wide.
  
  Ford Motor Company’s ethos is to compete to win, to enable this, a key priority is deriving meaningful insights from data. At Ford Halewood Transmissions Ltd, manufacturing data is the priority, this role embodies continuous improvement, enabling teams to adapt to the insights that you provide. You will be part of the plant manufacturing team and part of the wider data science pillar in Ford. You will be responsible for conceptualising, developing and maintaining a range of manufacturing data science projects and products.
  
  Qualifications and Experience required by the Manufacturing Data Scientist
  
  Essential:
  
  Degree level education in relevant subject (Mathematics, Statistics, Data Analytics, Computer Science a Physical Science or related) or equivalent experience relevant to the field in an engineering/automotive environment.
  
  Essential:
  
  Python expertise
  
  Essential:
  
  Expertise using ML techniques
  
  Essential:
  
  Experience using statistical methodologies
  
  Preferable:
  
  SQL proficiency
  
  Preferable:
  
  Cloud computing proficiency
  
  Key Responsibilities (including but not limited to):
  
  Ford+ Behaviours and leadership
  
  
• Demonstrate Ford+ Behaviours in daily work: ownership, collaboration, customer focus, integrity, inclusion, and learning. Role-model these behaviours in cross-functional projects and in mentoring others.
  
  
• Lead or co-lead cross-site analytics initiatives, sharing best practices and building a plant-level analytics playbook.
  
  Data collection, transformation, and governance
  
  
• Extract, transform, load, analyse, and report complex manufacturing data from multiple sources.
  
  
• Establish and maintain data quality checks, metadata, lineage, governance, and security controls to ensure trustworthy analytics.
  
  Insight generation and storytelling
  
  
• Identify bottlenecks and variability drivers to improve OEE, yield, scrap reduction, downtime, cycle times, and energy usage.
  
  
• Develop and maintain dashboards and visualisation for plant leadership, engineers, and operators; communicate findings in clear, non-technical terms.
  
  Modelling, experimentation, and impact
  
  
• Build and deploy predictive and prescriptive models (predictive maintenance, yield/defect forecasting, anomaly detection, capacity planning, SPC-aware models).
  
  Deployment, governance, and scale
  
  
• Operationalise models in the cloud with robust MLOps practices, including versioning, monitoring, drift detection, retraining, and documentation.
  
  
• Create model cards and explainability artifacts to support trust and adoption by operators and leadership.
  
  
• Develop scalable data pipelines and reusable analytics components; enable near real-time scoring and alerting for process deviations.
  
  Collaboration, enablement, and change management
  
  
• Partner with process engineers, maintenance, quality, IT, production, and supply chain to translate analytics into actions.
  
  
• Support pilots and scale successful solutions across sites; deliver training and skill development in analytics across the plant.
  
  Compliance, safety, and ethics
  
  
• Ensure data privacy, security, and regulatory/compliance considerations are integrated into analytics work.
  
  
• Promote data governance, documentation of data sources, assumptions, and limitations, champion safe and ethical use of data and models.
  
  Communication and stakeholder engagement
  
  
• Translate technical results into business impact, tailor communications for varying levels of statistical literacy across teams.
  
  
• Proactively identify gaps in current processes and propose concrete steps to close them; foster a culture of continuous improvement.
  
  People and capability development
  
  
• Contribute to building a digital/data science team within the plant; deploy analytics training and upskilling across departments.
  
  About Ford
  
  Ford Motor Company is a global automotive industry leader that manufactures or distributes vehicles across six continents. With over 200,000 employees and 65 plants worldwide, the UK employ over 13,000 individuals.
  
  The Ford+ plan is transforming the business to align the global organisation into an integrated team to accelerate. This is by focusing on the creation of vehicles revising the customers true demands, reduction of costs, to introduce exciting new technology, enhance quality and improve efficiency.
  
  About Ford Halewood Transmission Limited
  
  Ford Halewood Transmission Limited (FHTL) develops and manufactures transmissions with an employee workforce of circa 600 people. The Plant has a proud 60-year history as a local employer and are dedicated to manufacturing high quality products. Ford are currently investing up to £230 million at the facility to transform it to build electric power units for future Ford all-electric passenger and commercial vehicles.
  
  Future Prospects
  
  The business invests significantly in its employee development.
  
  FHTL supports the onward development and growth of all personnel and has a track record of promoting from within based on performance and achievement.
  
  Proposed start date:
  
  ASAP – Based on personal availability if you accept the offer of employment.
  
  The Company is committed to diversity and equality of opportunity for all and is opposed to any form of less favourable treatment or harassment on the grounds of race, religion or belief, sex, marriage and civil partnership, pregnancy and maternity, age, sexual orientation, gender reassignment or disability. This vacancy is advertised in line with the FORD equal opportunities policy.
  
  To apply for the Manufacturing Data Scientist role please click apply now and please ensure that you apply for this position via one recruitment agency only