Cheminformatics & Python Solutions Developer

Develop scientific software and automate chemistry workflows to support molecular research and digital transformation initiatives. Combine strong Python development skills with chemistry domain expertise. Curate, standardize, validate, and modify chemical structures and associated molecular data. Support chemistry data management, scientific computing, and AI/ML research initiatives., Curate, validate, and maintain chemical structure data across research platforms and scientific workflows. Perform chemical structure standardization and normalization, including: Salt and solvent handling Valence checks Charge normalization Tautomer treatment Stereochemistry review Duplicate identification Support compound registration, structure correction, and structure modification. Manage molecular metadata and ensure data accuracy and consistency. Investigate and resolve chemistry data-quality issues in collaboration with medicinal chemists, computational scientists, and informatics teams. Define and implement repeatable quality-control rules for chemistry datasets used in analytics and AI/ML initiatives.

1. Python Development and Automation Design and develop Python-based applications, APIs, libraries, and automated workflows for chemistry and scientific data processing. Build scalable pipelines for chemical structure ingestion, transformation, validation, standardization, and export. Integrate chemistry platforms, scientific databases, and enterprise or cloud services using APIs and data-integration patterns. Develop modular, tested, maintainable code following software development best practices. Participate in code reviews, technical documentation, release management, and production support. Create scientist-friendly utilities, notebooks, and lightweight interfaces to reduce manual curation effort and improve traceability.

2. Cheminformatics and Scientific Computing Use RDKit, ChemAxon, or equivalent tools for molecular analysis and chemical structure processing. Develop capabilities for: Substructure and similarity searches Molecular scaffold analysis Molecular descriptor calculation Compound clustering Molecular property computation Apply chemistry domain knowledge to ensure software outputs are scientifically accurate and meaningful. Support data preparation and feature-generation workflows for predictive modeling and molecular design. Contribute to AI-enabled research and machine learning initiatives in pharmaceutical discovery.

3. Stakeholder Collaboration and Delivery Collaborate with chemists, informaticians, data scientists, product owners, and software engineers. Translate scientific and business requirements into technical solutions. Participate in solution design, effort estimation, development, testing, and validation. Support deployment, operational activities, and ongoing software maintenance. Communicate technical decisions and scientific data-processing approaches effectively to technical and non-technical stakeholders.

Strong experience in Python development, including applications, APIs, libraries, and automated workflows. Knowledge of cheminformatics and chemical structure processing. Experience with cheminformatics toolkits such as: RDKit ChemAxon Equivalent cheminformatics technologies Understanding of chemical structures, molecular properties, stereochemistry, and compound metadata. Experience with data ingestion, transformation, validation, standardization, and export pipelines. Knowledge of API integration, scientific databases, and enterprise or cloud services. Experience writing modular, tested, maintainable, and production-ready code. Familiarity with code reviews, documentation, release management, and production support. Understanding of data preparation and feature-generation workflows for predictive modeling, molecular design, and AI-enabled research., Python Development Cheminformatics RDKit and ChemAxon Chemical Structure Curation and Standardization Molecular Data Management Compound Registration and Metadata Management Stereochemistry and Tautomer Handling Molecular Descriptors and Property Computation Substructure and Similarity Searching Scaffold Analysis and Compound Clustering Scientific Data Pipelines and Automation API Development and Integration Data Quality and Validation AI/ML Data Preparation Predictive Modeling and Molecular Design Pharmaceutical Research and Development Cross-functional Collaboration and Technical Documentation