Manufacturing Data Scientist

Overview

In this role you will shape the future of automotive manufacturing by applying machine learning, advanced analytics and data-driven decision making to optimise processes across Ford’s Europe PTME network. You will own analytical projects from problem definition to deployment, collaborating with engineers, manufacturing specialists and business stakeholders. The role blends data science with real-world manufacturing problem solving in a hybrid, travel-enabled environment. You will contribute to a data-driven culture that drives operational excellence and continuous improvement.

Responsibilities

• Develop and maintain ML, statistical and forecasting models to optimise manufacturing processes and extract actionable insights from equipment, process and operational data
• Design and build scalable data pipelines using Python and Google Cloud Platform to ingest, transform and prepare data for analysis and deployment
• Interface with internal and external stakeholders to translate challenges into analytical solutions
• Facilitate requirements gathering, manage expectations and support adoption of analytical solutions
• Standardise data via cleansing and reconciliation across diverse manufacturing systems
• Support launches of new processes, equipment and programmes with data-driven insights
• Present findings and recommendations to technical and non-technical audiences
• Collaborate with innovation, software, data engineering and enterprise data teams to ensure scalability and alignment with tech strategy
• Mentor peers and document knowledge to support long-term capability growth
• Drive a culture of continuous learning, collaboration and data-driven decision making
• On-site execution: travel to Ford plants and suppliers globally as required

Key requirements

• Strong proficiency in Python for data analysis, ML and statistical modelling (pandas, NumPy, scikit-learn)
• Experience with cloud-based data platforms, preferably Google Cloud
• Proven experience delivering analytical, statistical or ML solutions in complex operations
• Ability to lead analytical projects end-to-end from problem definition to deployment and adoption
• Excellent communication and stakeholder management skills
• Hands-on experience building scalable data pipelines and analytical data products
• Strong problem solving and ability to translate business problems into analytical frameworks
• Preferred: manufacturing, IoT, Industry 4.0 data environment knowledge and automotive/battery domain experience

• communication
• stakeholder management
• collaboration
• Python
• pandas
• NumPy

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