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Senior Cheminformatics Python Engineer / Chemistry Data Engineer

Purple Drive

Role Descriptions: Key Responsibilities
  • Chemistry Data Curation & Structure Management
  • Curate, 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 Computing
  • Use 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 & Delivery
  • Partner 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 Qualifications
  • Master'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 Qualifications
  • Experience 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 Competencies
  • Python engineering and scientific software development
  • Chemistry curation and molecular data quality
  • Cheminformatics and structure-processing workflows
  • Analytical problem-solving across chemistry data and code
  • Collaboration with scientific and technology stakeholders
  • Delivery of reliable, documented, and maintainable solutions
Measures of Success
  • Higher 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.
Vacancy posted 23 days ago
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