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: • Measured OEE gains and throughput/capacity improvements • Digital PID tuning outcomes for reactors/critical loops with validated benefits • Predictive maintenance models reducing unplanned downtime • Automated scheduling or optimisation tools that respect plant constraints • Real‑time plant performance dashboards with actionable insights
Additional Information: • Travel to plant sites as required for trials, commissioning, and operator training. • Role involves time in operating areas; adherence to all EHS requirements is mandatory.
Working Relationships: • Internal: Production, Maintenance, Engineering, EHS, Supply Chain/Planning, IT/OT • External: Vendors/consultants for DCS, historians, and simulation; academic/industry partners as needed.
Success Measures (12–18 Months) • Quantified improvements in throughput, yield, quality, or energy with validated financial impact • Stable deployment of at least two production-grade analytics/optimisation solutions integrated with plant systems • Robust MLOps/monitoring in place (drift detection, retraining cadence) • 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.
Top Skills
What We Do
Synthomer is a business-to-business speciality chemicals producer. We create value for all our stakeholders by applying our expertise and innovation capabilities to provide high-performance water-based polymers and ingredients to a wide range of blue-chip customers in multiple attractive end markets.
Synthomer are headquartered and stock listed in the UK. We have more than 30 operational sites across Americas, Europe, the Middle East and Asia including four innovation centres of excellence. The Company employs around 4,200 entrepreneurial, highly skilled employees with the expertise and experience to drive our success worldwide.
