Materials & Polymers Domain Specialist

About the role

Patsnap is developing high-fidelity datasets for materials science by extracting information from scientific literature and patents, beginning with a focus on engineering polymers. You will lead this program by managing external vendors, ensuring scientific accuracy, and integrating data into our ontology and search systems. This is a technical position requiring deep chemical expertise to resolve complex structural and property-related data challenges.

Key facts

What you'll do

• Direct the polymer curation program by defining annotation standards, setting delivery timelines, and establishing acceptance criteria for internal and external teams.
• Monitor project performance, including throughput, budget, and error rates, to ensure pilot objectives are met.
• Design and execute quality control protocols, including gold-standard adjudication and inter-annotator agreement measurements.
• Review complex cases involving Markush structures, composition tables, and measurement contexts to refine AI extraction and dictionary rules.
• Manage data contracts and normalization rules while resolving ontology gaps in collaboration with the ontology team.
• Partner with product and search teams to integrate curated relationships into our query and indexing infrastructure.
• Apply these quality and delivery standards to expand the portfolio into additional materials domains.

Requirements

• Masters degree in polymer science, chemistry, materials science, or chemical engineering, or a Bachelors degree with equivalent industry experience.
• Proficiency in interpreting structural units, including bracket notation, attachment points, and end groups.
• Ability to analyze Markush structures, R-groups, and generic patent claims.
• Understanding of polymer architectures such as linear, branched, block, graft, random, and network structures.
• Skill in parsing formulation descriptions, including constituent roles, base polymers, additives, and various quantity bases like wt% or phr.
• Capability to accurately bind properties to the correct sample or component within complex data tables.
• Proven experience managing quality through structured systems like ISO, GLP, or formal audit-ready workflows.
• Experience managing projects, teams, or external partners against specific deliverables and schedules.

Nice to have

• Experience evaluating AI or machine learning extraction outputs, such as LLM performance or precision and recall metrics.
• Background in managing distributed or outsourced annotation teams.
• Familiarity with knowledge graphs, OWL, SKOS, or entity resolution.
• Proficiency in Python or similar scripting languages for automating QC and validation tasks.
• Knowledge of information retrieval or search relevance evaluation techniques.
• Experience with cheminformatics tools including structure normalization, SMILES, or InChI.

Skills & tools

• Polymer structure and representation
• Patent analysis and interpretation
• Quality control and process management
• Project and vendor management
• Data ontology and schema management

Practical notes

Candidates will be tested on their scientific judgment using real patent examples during the interview process. We provide training on curation mechanics, Patsnap data schemas, patent data conventions, and search-evaluation concepts.