Job Description

Main Accountabilities:


1. Model Development & Deployment: Design, build, and maintain machine learning and optimisation models for real manufacturing problems (e.g., soft sensors, quality prediction, set?point optimisation, scheduling solvers).


2. Control Integration: Validate and deploy digital PID tuning recommendations; integrate analytics outputs with DCS/PLC and plant historians for closed?loop or advisory control.


3. Simulation & Digital Twin: Develop and maintain Aspen (or equivalent) steady?state/dynamic models; support digital twin use cases for scenario analysis and process optimisation.


4. Data Engineering for Operations: Ensure data availability, structure, and quality across historians, MES, LIMS, ERP; build reliable pipelines for near real?time and batch analytics.


5. Change Management & Adoption: Partner with production and maintenance to operationalise models (MLOps), verify impact, and embed solutions into standard work.


6. Performance Visibility: Deliver intuitive dashboards and alerts that expose leading indicators, constraints, and improvement opportunities.


7. Sustain & Improve: Monitor drift, retrain models, and continuously improve based on new data and evolving process conditions.


Expected Deliverables: o Measured OEE gains and throughput/capacity improvements o Digital PID tuning outcomes for reactors/critical loops with validated benefits o Predictive maintenance models reducing unplanned downtime o Automated scheduling or optimisation tools that respect plant constraints o Real?time plant performance dashboards with actionable insights


Additional Information: o Travel to plant sites as required for trials, commissioning, and operator training. o Role involves time in operating areas; adherence to all EHS requirements is mandatory.


Working Relationships: o Internal: Production, Maintenance, Engineering, EHS, Supply Chain/Planning, IT/OT o External: Vendors/consultants for DCS, historians, and simulation; academic/industry partners as needed.


Success Measures (12-18 Months) o Quantified improvements in throughput, yield, quality, or energy with validated financial impact o Stable deployment of at least two production-grade analytics/optimisation solutions integrated with plant systems o Robust MLOps/monitoring in place (drift detection, retraining cadence) o Positive feedback from operations on usability and adoption

Why Synthomer?

We are ambitious!

We have grown significantly - both organically and inorganically. We are a FTSE 250 listed company, 22% of our revenue comes from newly commercialized products, and we're recognized in the top-quartile for chemicals manufacturing safety.

We believe in high challenge, high support!

We are keen to let you contribute in real roles from day 1. We expect a lot, but offer a lot, too. This includes onboarding, induction and learning events, networking opportunities, mentoring and personal development planning. So, be up for an inspiring long-term career adventure.

We personalize our approach to development!

At Synthomer, you won't find generic career tracks or development programs but rather a one-size-fits-one approach to employee development. We'll partner with you to ensure you have the right experiences that build your capabilities and accelerate your career growth.