Senior Cheminformatics Python Engineer / Chemistry Data Engineer

Senior Cheminformatics Python Engineer / Chemistry Data EngineerGroton, CTRole Descriptions: Key ResponsibilitiesChemistry Data Curation & Structure ManagementCurate, validate, and maintain chemical structure data used across research platforms and scientific workflows.Perform structure standardization and normalization, including salt or solvent handling, valence checks, charge normalization, tautomer treatment, stereochemistry review, and duplicate identification.Support compound registration, structure correction, structure modification, and molecular metadata management.Investigate and resolve data-quality issues in collaboration with medicinal chemists, computational scientists, and informatics teams.Define and apply repeatable quality-control rules for chemistry datasets used in analytics and AI/ML initiatives.Python Development & Automation:Design and develop Python-based applications, APIs, libraries, and automated workflows for chemistry and scientific data processes.Build scalable pipelines for structure ingestion, transformation, validation, standardization, and export.Integrate chemistry platforms, scientific databases, and enterprise or cloud services using APIs and data-integration patterns.Write modular, tested, maintainable code and contribute to code reviews, documentation, release practices, and production support.Create scientist-friendly utilities, notebooks, or lightweight interfaces that reduce manual curation effort and improve traceability.Cheminformatics & Scientific ComputingUse cheminformatics toolkits such as RDKit, ChemAxon, or equivalent technologies for molecular analysis and structure processing.Develop capabilities for substructure and similarity search, scaffold analysis, descriptor calculation, compound clustering, and molecular property computation.Apply chemistry knowledge to ensure software outputs are scientifically meaningful and fit for use.Contribute to data preparation and feature-generation workflows supporting predictive modeling, molecular design, and AI-enabled research.Stakeholder Collaboration & DeliveryPartner with chemists, informaticians, data scientists, product owners, and software engineers to translate scientific needs into technical solutions.Participate in solution design, estimation, development, testing, validation, deployment, and operational support.Communicate technical decisions, chemistry-data risks, and delivery status clearly to scientific and technology stakeholders.Promote reusable engineering patterns, chemistry-data standards, and continuous improvement.Required QualificationsMaster's degree or PhD in Chemistry, Cheminformatics, Computational Chemistry, Pharmaceutical Sciences, Computer Science with substantial chemistry experience, or a related discipline. Equivalent relevant industry experience may be considered.Strong professional experience developing production-quality solutions in Python.Solid grounding in organic chemistry and chemical structure representation, including stereochemistry, salts, tautomers, charges, and structure-quality concepts.Hands-on experience with chemistry curation, compound registration, structure standardization, or molecular data management.Experience with Python scientific and data libraries such as pandas and Jupyter, plus SQL and REST APIs.Experience with at least one cheminformatics toolkit or chemistry platform, such as RDKit, ChemAxon, BIOVIA Pipeline Pilot, Dotmatics, Signals, or an equivalent platform.Ability to work across scientific and technical teams and explain complex concepts to varied audiences.Preferred QualificationsExperience supporting pharmaceutical or life-sciences R&D, particularly small-molecule discovery or chemical synthesis workflows.Familiarity with compound registration systems, ELN platforms, chemical inventory tools, or scientific data platforms.Knowledge of cloud platforms, containers, CI/CD, automated testing, and secure software-development practices.Exposure to AI/ML applications involving molecular data, property prediction, molecule generation, or synthesis planning.Understanding of scientific data governance, auditability, validation, and regulated-environment expectations.Core CompetenciesPython engineering and scientific software developmentChemistry curation and molecular data qualityCheminformatics and structure-processing workflowsAnalytical problem-solving across chemistry data and codeCollaboration with scientific and technology stakeholdersDelivery of reliable, documented, and maintainable solutionsMeasures of SuccessHigher quality, consistency, and traceability of curated chemistry data.Reduced manual effort through dependable Python automation and self-service tools.Scalable, maintainable chemistry workflows that meet scientist and business needs.Effective connection between chemistry subject-matter experts and engineering teams.Reusable data and software foundations that support analytics and AI-enabled molecular research.