Applied Data Scientist

About CPI CPI helps make great ideas and inventions a reality. We’re a team of intelligent people using advances in science and technology to solve the biggest global challenges in healthcare and sustainability. Through our incredible people and innovation infrastructure, we collaborate with our partners in industry, academia, government, and the investment community to accelerate the development and commercialisation of innovative products. From health technologies and pharmaceuticals to sustainable food and materials innovations, we turn the entrepreneurial spirit and radical thinking of our people and partners into incredible impact that makes our world a better place. Why this role is important for CPI’s work 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 facility. 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. Reporting to a Team Leader, you will leverage your existing skills in data science and be further developed in strategically relevant areas such as Machine Learning (ML), Artificial Intelligence (AI), predictive modelling, automation of data capture/processing, and ML‑driven Design of Experiments (DOE) methods. Using these skills across a combination of low‑code platforms, Python scripts, and cloud‑based technologies for scalable computation and data management, you will contribute to the delivery of innovation projects with our clients and support technical leads in providing advice and solutions to both internal and external stakeholders. In addition, this role offers a unique opportunity to contribute to the development and operation of our 24/7 robotic formulation laboratory, integrating advanced automation with data‑driven experimentation to serve our markets. Some exciting projects the team have recently worked on are: • BATTERY 2030 + Roadmap: creating a digital twin for battery manufacturing that integrates data‑driven and physics‑based methods. It develops a cross‑chemistry data space for two technologies, Li‑ion and Na‑ion coin cells and redox flow batteries. • EU project developing advanced sensing, monitoring and self‑healing mechanisms to self‑repair batteries, leading to the EU batteries of the future. • LNP manufacture for supporting RNA vaccines and therapeutics. • Facility for battery manufacture and analysis from the formulation through to the cell manufacturing served by collaborative mobile robots. Other types of projects that we run include: Working with global leaders to apply model predictive control to their formulations. Using clustering and correlation analysis to determine cause‑effects or comparisons within datasets (e.g., developing models to predict soap stability, predicting best candidates for new ink materials). Supporting development of our automated platforms in service of our markets. Using machine learning techniques to analyze data to produce actionable insights. Developing soft sensors based on PLS and neural‑net models to predict slurry particle size and viscosity. Implementing Bayesian methods and/or state‑of‑the‑art methods for optimising the Design of Experiments approach. Developing a federated learning system to produce global models that enhance production in manufacturing. 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 research, then analysing, interpreting and reporting the results. Keeping up to date with research and techniques relevant to the digital space (e.g., developing in statistical modelling techniques, 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, 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 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. What does CPI offer you? Up to 36 days holiday, including bank holidays – Plus a holiday purchasing scheme. Generous pension scheme. Life assurance and accident insurance schemes. Flexible working. Learning and Development Opportunities. Free parking. Additional Information Internal job title will be Research Engineer 1 – Digital Technologies / Research Engineer 2 – Digital Technologies (appropriate to experience level determined at interview stage). Research Engineer 1 – Digital Technologies (26,000 – 34,000 £) / Research Engineer 2 – Digital Technologies (up to 40,500 £). CPI is an organisation based in the UK. Commencement of employment is conditional to demonstrating right to work in the UK, sponsorship may be available. #J-18808-Ljbffr