Formulation Domain Specialist (Knowledge Architect)

About the role

Patsnap's Materials team builds structured formulation knowledge from patents, scientific literature and technical sources to support its Formulation Agent, which helps scientists turn product targets, existing formulas, required claims and ingredient constraints into evidence-backed formulation directions. You will define how this knowledge is represented and evaluated, working with formulation scientists, data scientists, engineers and product managers. This is an in-office position in the Singapore office.

Key responsibilities

• Define and maintain the knowledge model for formulations, covering ingredients, functions, concentrations, processes, properties, test methods and performance results.
• Establish evidence and quality standards, including how proposed, prepared and tested formulations are distinguished and how provenance, confidence and conflicting information are represented.
• Develop normalization rules that connect formulation information across patents, scientific literature, datasheets and other technical sources.
• Build guidelines, benchmarks and evaluation datasets for formulation extraction, search and AI-generated outputs.
• Work with product, data science and engineering teams to turn expert judgment and user feedback into improvements to the data and product.
• Lead the review and resolution of complex formulation-data questions and support the quality management of internal or external curation work.

Required profile

• Degree in formulation science, chemistry, polymer science, materials science, chemical engineering, pharmaceutical science, cosmetic science or a related field.
• At least 5 years of relevant experience in formulation R&D, scientific information analysis, technical data curation or knowledge management.
• Strong understanding of formulation design, including ingredient functions, concentrations, processing conditions, test methods and performance relationships.
• Ability to evaluate evidence across patents, scientific papers, technical datasheets and experimental records.
• Experience developing structured domain knowledge through schemas, taxonomies, controlled vocabularies, normalization rules or similar approaches.
• Professional working proficiency in English and Chinese.

Nice to have

• Hands-on experience developing or troubleshooting formulations in cosmetics, chemicals, coatings, polymers or pharmaceuticals.
• Experience with formulation informatics, experimental data management, design of experiments, ELN or LIMS systems.
• Experience with knowledge graphs, entity resolution, chemical structure data, information retrieval or search evaluation.
• Familiarity with how LLM-based products retrieve, evaluate and use scientific knowledge.
• Experience with patent analysis, prior-art search, novelty assessment or freedom-to-operate analysis.