Applied Data Scientist (Research Engineer – Digital Technologies)

Centre for Process Innovation; England; On-site; GBP 45,000 - 70,000; Full time

Job summary

A leading research organisation in the UK is seeking an Applied Data Scientist to join their digital team. The role demands expertise in data science, with a focus on statistical methods and machine learning applications across sectors such as energy storage and materials science. Candidates with a background in scientific, engineering, or mathematical disciplines will excel in this role. The position offers opportunities for professional growth and collaboration within a dynamic team environment, making it ideal for innovative thinkers eager to tackle real-world challenges using data.

Qualifications

• Educated to HNC / Foundation Degree / Degree level in a relevant discipline.
• Experience in the application of data science.
• Ability to apply theoretical and practical scientific methods.

Responsibilities

• Support the planning and scoping of digital strategy work programmes.
• Deliver technical programmes of work in data analytics and machine learning.
• Develop and improve existing data science methods.

Skills

Statistical methods

Machine learning

Coding languages (Python, R, MATLAB)

Data analytics

Education

HNC / Foundation Degree / Degree in Scientific, Engineering or Mathematical discipline

Tools

Cloud technologies

Job description

Overview

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 modelling, or data‑driven simulation on cloud platforms to address real‑world materials challenges will allow you to make an immediate impact.

The Role

• 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 data 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 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

• 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.