Applied Data Scientist (Research Engineer – Digital Technologies)
| Posting date: | 19 December 2025 |
|---|---|
| Salary: | £26,000 to £40,500 per year |
| Hours: | Full time |
| Closing date: | 11 January 2026 |
| Location: | Sedgefield, Stockton-On-Tees |
| Remote working: | On-site only |
| Company: | Centre for Process Innovation |
| Job type: | Permanent |
| Job reference: | CPI-11384-25 |
Summary
Please see our Careers page for full advert.
CPI has an exciting opportunity for an Applied Data Scientist (Research Engineer – Digital Technologies) to join its established and growing Automation and Digital team within the Formulation Technology Team at our state of the art: National Formulation Centre, based at NETPark in Sedgefield.
The ideal candidate will be a cross-disciplinary thinker, combining expertise in chemistry, physics, biology, or mathematics with strong data science skills. In this role, you will leverage modern computational, statistical, and cloud-based technologies to generate insights into complex materials, driving innovations across energy storage, sustainable materials, nanotherapeutics, and consumer goods. A strong foundation in materials at the molecular, atomic, or structural level is highly valued, along with a keen interest in the markets we serve — particularly energy storage, pharmaceuticals, and sustainable materials. Experience in applying machine learning, high-dimensional modeling, or data-driven simulation on cloud platforms to address real-world materials challenges will allow you to make an immediate impact.
The Role
Key tasks in the role will include (but are not limited to the below), please download the job description for full details available on the CPI careers page:
Supporting the planning and scoping of technical work programmes within digital strategy (e.g. model predictive control, process modelling, data analytics, machine learning, and the application of digital technologies).
Undertaking the technical delivery of programmes of work in digital strategy on existing data or data collected from own experiments and researches, and then analysing, interpreting and reporting the results.
Keeping up to date with research and techniques relevant to the digital space (e.g. develop in statistical modelling techniques, the mathematical foundations of applied machine learning, skills in process modelling and control, skills in relevant coding languages) and to develop, implement and improve existing methods/technologies in the platform.
Growing as an internal expert in data science using knowledge of principles and practices in the field to support non-data science colleagues.
Developing and utilising own expertise to build data science capability within the technology team and acting as internal consultant to coach others at CPI.
The person we are seeking
The successful candidate will be educated to HNC / Foundation Degree / Degree level (or equivalent) in a Scientific, Engineering or Mathematical discipline, plus relevant industrial experience in the application of data science in the prerequisite fields (see job descriptions for further information) and;
Will be able to solve and contextualise scientific problems using data science.
Will possess willingness to learn new methods of datra science and coding languages.
Can demonstrate the ability to apply theoretical and practical scientific methods to contribute to business activities.
Will have confidence to use own judgement and initiative within standard engineering / scientific practices, as well as an understanding of when to seek advice from colleagues.
Will possess knowledge of / have an awareness of one or more of the following data science and digital skills application methods;
The application of advanced statistical methods (e.g. PCA) and modelling to technical problem-solving.
The mathematical foundations of applied machine learning
The application of machine learning, process modelling or implementation of model predictive control.
The use of coding languages (python, R Matlab) to create digital solutions for efficient or novel problem solving.
The demonstration of technical and theoretical knowledge in mathematics related to data science
Can demonstrate a working knowledge of the principles and practices in data science techniques gained through academia / career to date .
Will have a background in / knowledge relevant to the batteries, energy storage and/or materials spaces
Can demonstrate evidence of building knowledge sharing and communicating with non-specialist colleagues and stakeholders.
Applications are particularly welcome from candidates who are educated to Masters/PhD level (or equivalent) with relevant industrial experience and;
• Have some experience in using data science on cloud architectures
• Have chartered status with a relevant professional institution
• Are a member of a relevant professional body
CPI has an exciting opportunity for an Applied Data Scientist (Research Engineer – Digital Technologies) to join its established and growing Automation and Digital team within the Formulation Technology Team at our state of the art: National Formulation Centre, based at NETPark in Sedgefield.
The ideal candidate will be a cross-disciplinary thinker, combining expertise in chemistry, physics, biology, or mathematics with strong data science skills. In this role, you will leverage modern computational, statistical, and cloud-based technologies to generate insights into complex materials, driving innovations across energy storage, sustainable materials, nanotherapeutics, and consumer goods. A strong foundation in materials at the molecular, atomic, or structural level is highly valued, along with a keen interest in the markets we serve — particularly energy storage, pharmaceuticals, and sustainable materials. Experience in applying machine learning, high-dimensional modeling, or data-driven simulation on cloud platforms to address real-world materials challenges will allow you to make an immediate impact.
The Role
Key tasks in the role will include (but are not limited to the below), please download the job description for full details available on the CPI careers page:
Supporting the planning and scoping of technical work programmes within digital strategy (e.g. model predictive control, process modelling, data analytics, machine learning, and the application of digital technologies).
Undertaking the technical delivery of programmes of work in digital strategy on existing data or data collected from own experiments and researches, and then analysing, interpreting and reporting the results.
Keeping up to date with research and techniques relevant to the digital space (e.g. develop in statistical modelling techniques, the mathematical foundations of applied machine learning, skills in process modelling and control, skills in relevant coding languages) and to develop, implement and improve existing methods/technologies in the platform.
Growing as an internal expert in data science using knowledge of principles and practices in the field to support non-data science colleagues.
Developing and utilising own expertise to build data science capability within the technology team and acting as internal consultant to coach others at CPI.
The person we are seeking
The successful candidate will be educated to HNC / Foundation Degree / Degree level (or equivalent) in a Scientific, Engineering or Mathematical discipline, plus relevant industrial experience in the application of data science in the prerequisite fields (see job descriptions for further information) and;
Will be able to solve and contextualise scientific problems using data science.
Will possess willingness to learn new methods of datra science and coding languages.
Can demonstrate the ability to apply theoretical and practical scientific methods to contribute to business activities.
Will have confidence to use own judgement and initiative within standard engineering / scientific practices, as well as an understanding of when to seek advice from colleagues.
Will possess knowledge of / have an awareness of one or more of the following data science and digital skills application methods;
The application of advanced statistical methods (e.g. PCA) and modelling to technical problem-solving.
The mathematical foundations of applied machine learning
The application of machine learning, process modelling or implementation of model predictive control.
The use of coding languages (python, R Matlab) to create digital solutions for efficient or novel problem solving.
The demonstration of technical and theoretical knowledge in mathematics related to data science
Can demonstrate a working knowledge of the principles and practices in data science techniques gained through academia / career to date .
Will have a background in / knowledge relevant to the batteries, energy storage and/or materials spaces
Can demonstrate evidence of building knowledge sharing and communicating with non-specialist colleagues and stakeholders.
Applications are particularly welcome from candidates who are educated to Masters/PhD level (or equivalent) with relevant industrial experience and;
• Have some experience in using data science on cloud architectures
• Have chartered status with a relevant professional institution
• Are a member of a relevant professional body
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