Cheminformatics Automation Engineer

Job Details

• Location:
  
  Groton, CT
• Duration: 6 months
• GBaMS ReqID:

• Chemistry Data Curation & Structure Management
• Curate, validate, and maintain chemical structure data across research platforms and scientific workflows.
• Perform structure standardization and normalization, including:
• Salt and solvent handling
• Valence checks
• Charge normalization
• Tautomer treatment
• Stereo chemistry review
• Duplicate identification
• Support:
• Compound registration
• Structure correction
• Structure modification
• Molecular metadata management
• Investigate and resolve data-quality issues with:
• Medicinal chemists
• Computational scientists
• Informatics teams
• Define and apply repeatable QC rules for chemistry datasets used in analytics and AI/ML initiatives.

• Design and develop Python-based:
• Applications
• APIs
• Libraries
• Automated workflows
• Build scalable pipelines for:
• Structure ingestion
• Transformation
• Validation
• Standardization
• Export
• Integrate chemistry platforms, scientific databases, enterprise systems, and cloud services through APIs.
• Write modular, tested, maintainable code.
• Participate in:
• Code reviews
• Documentation
• Release processes
• Production support
• Create scientist-friendly:
• Utilities
• Jupyter notebooks
• Lightweight interfaces
• Reduce manual curation effort and improve data traceability.

• Use cheminformatics toolkits such as:
• RDKit
• Chem Axon
• Equivalent technologies
• Develop capabilities for:
• Substructure search
• Similarity search
• Scaffold analysis
• Descriptor calculation
• Compound clustering
• Molecular property computation
• Apply chemistry knowledge to ensure software outputs are scientifically meaningful.
• Support data preparation and feature-generation workflows for:
• Predictive modeling
• Molecular design
• AI-enabled research

• Partner with:
• Chemists
• Informaticians
• Data scientists
• Product owners
• Software engineers
• Translate scientific requirements into technical solutions.
• Participate in:
• Solution design
• Estimation
• Development
• Testing
• Validation
• Deployment
• Operational support
• Communicate:
• Technical decisions
• Chemistry-data risks
• Delivery status
• Promote reusable engineering patterns and chemistry-data standards.
• Drive continuous improvement.

• Master's degree or PhD in:
• Chemistry
• Cheminformatics
• Computational Chemistry
• Pharmaceutical Sciences
• Computer Science with substantial chemistry experience
• Related discipline
• Equivalent relevant industry experience may be considered.
• Strong professional experience developing production-quality solutions in Python.
• Strong knowledge of:
• Organic chemistry
• Chemical structure representation
• Stereo chemistry
• Salts
• Tautomers
• Charges
• Structure quality
• Hands-on experience with:
• Chemistry data curation
• Compound registration
• Structure standardization
• Molecular data management
• Experience with:
• Python
• pandas
• Jupyter
• SQL
• REST APIs
• Experience with at least one cheminformatics toolkit or chemistry platform:
• RDKit
• Chem Axon
• BIOVIA Pipeline Pilot
• Dotmatics
• Signals
• Equivalent platform
• Ability to collaborate across scientific and technical teams.
• Ability to explain complex technical concepts to different audiences.

• Pharmaceutical or life-sciences R&D experience.
• Experience with small-molecule discovery or chemical synthesis workflows.
• Familiarity with:
• Compound registration systems
• ELN platforms
• Chemical inventory tools
• Scientific data platforms
• Knowledge of:
• Cloud platforms
• Containers
• CI/CD
• Automated testing
• Secure software development
• Exposure to AI/ML applications involving:
• Molecular data
• Property prediction
• Molecule generation
• Synthesis planning
• Understanding of:
• Scientific data governance
• Auditability
• Validation
• Regulated-environment expectations

• 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
• Reliable, documented, and maintainable solution delivery

• Improve quality, consistency, and traceability of curated chemistry data.
• Reduce manual effort through Python automation and self-service tools.
• Build scalable and maintainable chemistry workflows.
• Successfully bridge chemistry SMEs and engineering teams.
• Create reusable data and software foundations for:
• Analytics
• AI/ML
• Molecular research

• Python
• RDKit
• Cheminformatics
• Chemical Structure Curation
• Compound Registration
• Structure Standardization
• Structure Modification
• Molecular Data Management
• Medicinal…