Scientific Software Engineer

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.

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