Process Technology Engineer - Lubrizol Surface Science

Overview In this role you will advance Lubrizol’s Surface Science portfolio by enabling safe, scalable commercialization of natural and bio-based polymers. You will collaborate with R&D, Operations, Supply Chain, and Commercial teams to deliver robust manufacturing solutions. You will lead scale-up activities, apply data-driven methods to improve processes, and identify opportunities for safety, productivity, and quality gains. This position offers a chance to shape manufacturing capability and drive sustainable growth within a global, inclusive environment. Compensation / BenefitsCompetitive salary with performance-based bonus plans401(k) match + Age-Weighted Defined ContributionComprehensive medical, dental & vision coverageHealth Savings Account (HSA)Paid holidays, vacation, and parental leaveFlexible work environment ResponsibilitiesLead and support new product scale-ups through structured experimentation, pilot trials, and manufacturing authorization activitiesIdentify, benchmark, and deploy Most Effective Technologies (MET) to strengthen manufacturing capability and operational excellenceApply data-driven approaches (DOE, statistical analysis) to evaluate process performance and drive continuous improvementIdentify and implement opportunities to improve process safety, capability, productivity, quality, and costPartner with commercial and technical teams to align process technology strategies with business growth objectivesLead projects and present status updates, clearly communicating goals, progress, and results Key requirements8+ years of experience in chemical, specialty materials, or polymer manufacturing environmentsDemonstrated capability in experimental design, data analysis, and structured problem-solving methodologiesProven ability to collaborate effectively with cross-functional and geographically distributed teamsStrong written and verbal communication skillscross-functional collaborationclear communicationproblem-solvingexperimental designdata analysisDOE (design of experiments)