Data Scientist

16029

ScienceUnited KingdomCompetitivePermanent

Posted 0 days agoApply Now

We are currently supporting our client in their search for a Data Scientist to support the development and deployment of a digital twin platform for complex industrial process systems based on advanced separation and chemical engineering principles, along with analytical insights into the development of future technologies.
The successful candidate will work at the intersection of data science, process modelling, and chemical engineering to build predictive, physics-informed, and hybrid models that replicate and optimise real-world separation performance. This role is ideal for someone who enjoys translating process data into intelligent, operational decision-support systems.
Additional responsibilities include analysing experimental and pilot-scale data to support product development and performance characterisation.

Key roles and responsibilities:

Data engineering & analytics – collect, process and analyse sensor and process data across lab, pilot and plant scales
Digital twin development – support the development and validation of hybrid physicsML models for complex separation and chemical systems
Advanced modelling and optimisation – develop predictive models and apply optimisation algorithms to improve system recovery, energy and chemical usage, supported by scenario analysis
Deployment and integration collaborate with software engineers to deploy models into cloud or edge environments and support dashboard development and integration
Crossfunctional collaboration – translate engineering requirements into data science solutions and present findings to technical and nontechnical stakeholders

Candidate requirements

MSc or PhD in Data Science, Chemical Engineering, Computational fluid dynamics, Applied Mathematics, or related field
3+ years of experience in industrial data science or process modelling
Strong programming skills in Python (NumPy, Pandas, SciPy, scikitlearn, TensorFlow/PyTorch)
Experience with timeseries modelling and multivariate data analysis
Knowledge of statistical modelling, regression, classification, and optimization methods
Knowledge of equilibrium and kinetics modelling
Experience developing digital twins or hybrid modeling frameworks
Familiarity with process simulation tools (e.g., Aspen, gPROMS, MATLAB)
Experience with cloud platforms (AWS, Azure, GCP)
Strong problemsolving
Crossfunctional collaboration skills
Ability to manage multiple projects in a fastpaced R&D environment
Excellent technical documentation and communication skills

It is essential that applicants have the right to work in the UK. Due to the nature of the role, successful applicants will be subject to satisfactory background checks including a basic DBS check.

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Consultant

Phoebe Lole

With a background in Agriculture and Livestock Science, Phoebe began her career in the food and agriculture industry, working across FSQR, NPD, and supply chain before moving into a role supporting agricultural sustainability at a global food business. After several years in industry, she took a career break to work in the yachting sector - earning her Yachtmaster licence, skippering her own yacht, and progressing to superyachts.

Now part of the Science team at Jackson Hogg, Phoebe recruits across the UK for a wide range of science roles, ranging from lab technicians to regulatory directors, supporting clients across the life science sector. Outside of work, Phoebe enjoys hiking, trail running, and baking.

Consultant - Science

07897927166

phoebe.lole@jacksonhogg.com

Data Scientist

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