Manufacturing Data Scientist

Job-:
Manufacturing

Location:

Dunton, Essex, United Kingdom Workplace:
Hybrid

Schedule:

Full time Posted:
Preferred Degree:
Bachelor of Science Department The  Powertrain Manufacturing Engineering (PTME) Europe team is at the forefront of innovation, dedicated to equipping our manufacturing plants with world-leading systems. We are committed to modernising our business by designing and installing advanced manufacturing solutions that enable our plants to efficiently deliver our diverse portfolio of propulsion systems and cutting-edge battery solutions for vehicles.

As manufacturing becomes increasingly connected and data-driven, PTME plays a critical role in combining engineering expertise, advanced analytics and digital technologies to improve quality, productivity, equipment performance and operational excellence across our manufacturing network.

To support this mission, we are a travelling department with regular opportunities to work alongside manufacturing plants and suppliers across Ford's global operations.

Opportunity As a key member of our PTME team, you will play a crucial role in shaping the future of automotive manufacturing through machine learning, advanced analytics and data-driven decision making.

You will be responsible for identifying opportunities, developing analytical solutions and delivering measurable business outcomes across the full project lifecycle.

This role offers the unique opportunity to combine technical data science expertise with real-world manufacturing problem solving.

You will apply machine learning, statistical modelling and advanced analytics techniques to unlock insights from connected manufacturing data while working alongside a collaborative team of engineers, manufacturing specialists and business stakeholders.

PTME is looking for an individual who can help expand the use of data science throughout the organisation. You will collaborate with a team of over 100 manufacturing engineers and must be comfortable working directly with stakeholders both in our Dunton office and at manufacturing facilities.

This is not a traditional analytics role focused solely on model development. Successful candidates will be expected to take ownership from problem definition through data acquisition, solution development, deployment support and business adoption.

Hybrid Worker (minimum 4 days on-site per week)
Ability to travel domestically and internationally as required

Qualifications

Experience and skills for being effective in the role are:

Technical Proficiency:
Strong proficiency in Python for data analysis, machine learning and statistical modelling (e.g. pandas, Num Py, scikit-learn), alongside familiarity with cloud-based data platforms, preferably Google Cloud.

Analytical Modelling:
Proven experience developing analytical, statistical or machine learning solutions within complex operational environments, coupled with a strong desire to continuously improve model performance, data quality and business outcomes.

Project Execution:
Demonstrated ability to lead analytical projects from problem definition through development, deployment and business adoption.

Communication & Stakeholder Management:
Excellent communication and facilitation skills, with the ability to manage stakeholder expectations, influence decision making and work effectively in complex environments.

Data Engineering:
Hands-on experience building and maintaining scalable data pipelines and analytical data products using structured data engineering practices.

Problem Solving:
Ability to translate complex business problems into structured analytical frameworks, supported by a passion for uncovering insights and solving challenging real-world manufacturing problems.

Manufacturing Acumen & Domain Knowledge (Preferred):
Direct experience working with manufacturing, industrial, IoT, connected equipment or Industry 4.0 data environments.

Experience with in automotive, battery, propulsion systems or other advanced manufacturing sectors would be advantageous.

You will have:

Degree in Data Science, Computer Science, Engineering, Mathematics or a related quantitative discipline.

If you do not hold a degree but possess relevant skills and experience equivalent to this level of education, we would still welcome your application.

Additional Information Ability to travel periodically to Ford manufacturing plants and suppliers globally is essential.

This position is based in Dunton and it is expected the successful candidate will typically attend the office or…