About the Company: Join this team to partner with enterprise clients in deploying data-driven software that transforms technical and operational environments. This cross-functional role blends engineering expertise with customer engagement, data analysis, and technical problem-solving to drive measurable business impact. If you are excited about being at the forefront of technology and using AI to solve real problems, read on.

About the Role: You will collaborate directly with customer stakeholders to diagnose operational challenges, analyze production data, and build models that unlock efficiency. The ideal candidate thrives in cross-functional teams, translates complex data into actionable insights, and bridges the gap between technical capabilities and business value.

Responsibilities:

Customer Success: Lead technical onboarding and implementation, building trusted relationships with stakeholders to drive workflow optimization and operational improvements. Data & Modeling: Analyze operational datasets to uncover trends, developing Python-based models and simulations that inform strategic decisions. Experience in building mechanistic models (first principles) and statistical models. Collaboration: Partner with product and engineering teams to refine platform functionality and communicate technical findings to diverse audiences. Problem Solving: Support troubleshooting and continuous improvement initiatives in complex industrial settings, ensuring successful project delivery from discovery to deployment.

Qualifications:

Experience: 5–7 years in process engineering, manufacturing, or operations, ideally within the specialty chemicals sector (e.g., polymers, adhesives, coatings, surfactants, performance polymers, monomers, & adhesives, semiconductor and advanced materials). Experience in mechanistic modelling or digital twin simulation. Previous experience working as a Process Development Engineer, R&D Engineer or Data Scientist.

Role requirements:

Education: Degree in Chemical Engineering or a related technical field. Technical Skills: Proficiency in data analysis, modeling, and simulation tools, with strong fluency in Python. Experience using Aspen Plus, COMSOL, ANSYS, MATLAB/Simulink for building models. Industrial Knowledge: Familiarity with enterprise historians (e.g., OSIsoft PI, DeltaV, Wonderware, GE Proficy) is highly valued. Soft Skills: Excellent communication and project management abilities, with a proven track record of engaging directly with customers. Language: Fluency in French is a bonus.