R&D Engineer / Scientist

AdvanSix plays a critical role in global supply chains, innovating and delivering essential products for our customers in a wide variety of end markets and applications that touch people’s lives, such as building and construction, fertilizers, plastics, solvents, packaging, paints, coatings, adhesives, and electronics. Our reliable and sustainable supply of quality products emerges from the vertically integrated value chain of our three U.S. based manufacturing facilities. AdvanSix strives to deliver best-in-class customer experiences and differentiated products in the industries of nylon solutions, chemical intermediates, and plant nutrients, guided by our core values of Safety, Integrity, Accountability and Respect.

Please view a short video about our company here, AdvanSix Video. For more information on AdvanSix, please visit our website at http://www.advansix.com


Why work at AdvanSix?


• We provide benefits that are industry competitive and focused on employee well-being


• Total Rewards program includes a competitive compensation, health, dental, vision & wellness programs, paid vacation, 401K with company matching, health savings programs, disability & life insurance, employee assistance program


• Tuition reimbursement for continued education, certifications, training, and development


• Work within a fast paced and innovative company, meeting passionate colleagues and partners with diverse backgrounds and experiences


Nylon Lead R&D Scientist (Polymer Chemistry & Process Technology Focus)
Position Summary
The Nylon Lead R&D Scientist serves as a technical leader driving polymer chemistry innovation and process technology advancement for nylon (polyamide) systems. This role is responsible for developing deep molecular-level understanding and translating it into robust, scalable process solutions that improve manufacturing performance, product quality, and cost competitiveness.
Secondary responsibilities include new product development (NPD) and commercialization aligned with business strategy, with a strong emphasis on accelerating research cycles through advanced data analytics and AI-enabled experimentation.


Core Responsibilities
1. Polymer Chemistry Leadership (Primary Focus)
• Lead design and execution of polyamide synthesis reactions, including batch and continuous polymerization systems.
• Develop deep understanding of structure–property relationships to tailor polymer performance for target applications.
• Apply advanced analytical techniques (e.g., rheology, DSC, GPC, IR, NMR) to characterize materials and guide decision-making.
• Drive innovation in polymer modification, copolymerization, and additive incorporation to enable differentiated products.
• Serve as subject matter expert in polyamide chemistry, organic chemistry, and analytical chemistry across the organization.


2. Process Technology & Scale-Up (Primary Focus)
• Lead development and optimization of polymerization and downstream processing technologies (extrusion, compounding, molding).
• Translate laboratory discoveries into pilot and commercial-scale processes, ensuring consistency, yield, and cost efficiency.
• Provide technical leadership in process modeling, troubleshooting, and process improvement initiatives.
• Partner with plant, engineering, and production teams to:
◦ Improve conversion efficiency, throughput, and energy intensity
◦ Resolve process limitations and variability
◦ Enable reliable and repeatable manufacturing performance
• Apply statistical tools (Six Sigma, DOE) to drive process robustness and variability reduction.


3. AI-Enabled Experimental Design & Research Acceleration (Key Differentiator)
• Leverage artificial intelligence (AI) and machine learning tools to:
◦ Design optimized Designs of Experiments (DOE)
◦ Identify critical variables and interactions faster than traditional approaches
◦ Predict polymer properties and process outcomes
• Develop and deploy data-driven experimentation frameworks to reduce research cycle time and increase success rates.
• Integrate experimental data, process data, and analytical results into predictive models that guide decision-making.
• Continuously improve R&D efficiency through:
◦ Automated data analysis workflows
◦ Digital lab tools and experiment tracking systems
• Demonstrated history of using advanced analytics or AI methods to accelerate root cause analysis and experimental iteration cycles (aligned with structured DOE approaches observed internally).


4. New Product Development & Commercialization (Secondary Focus)
• Lead development of new nylon materials and