Cheminformatics Automation Engineer

Job Details

• Location: Groton, CT

• Duration: 6 months

• GBaMS ReqID: 10957906

Key Responsibilities

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

  • Stereochemistry 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.

Python Development & Automation

• 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.

Cheminformatics & Scientific Computing

• Use cheminformatics toolkits such as:

  • RDKit

  • ChemAxon

  • 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

Stakeholder Collaboration & Delivery

• 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.

Required Qualifications

• 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

  • Stereochemistry

  • 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

  • ChemAxon

  • BIOVIA Pipeline Pilot

  • Dotmatics

  • Signals

  • Equivalent platform

• Ability to collaborate across scientific and technical teams.

• Ability to explain complex technical concepts to different audiences.

Preferred Qualifications

• 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

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

• Reliable, documented, and maintainable solution delivery

Measures of Success

• 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

Suggested Search Keywords

• Python

• RDKit

• Cheminformatics

• Chemical Structure Curation

• Compound Registration

• Structure Standardization

• Structure Modification

• Molecular Data Management

• Medicinal Chemistry

• Scientific Computing

• Pharmaceutical R&D