Senior Scientist, Cheminformatics

Position Overview

Our Company is currently seeking an exceptional, highly motivated Senior Scientist, Cheminformatics to join the Modeling & Informatics group within Discovery Chemistry. The successful candidate will join multidisciplinary discovery teams to drive the development and application of advanced cheminformatics workflows, machine learning models, and data-driven methods. This role focuses on accelerating drug discovery pipelines across both small molecules and emerging modalities—such as cyclic peptides, macrocycles, and DNA-Encoded Library platforms—in close partnership with computational and medicinal chemists.

Key Responsibilities

• Computational Chemistry Partnership: Partner closely with computational and medicinal chemists on Discovery Chemistry project teams to address challenging structure-activity relationships and multi-parameter optimization
• Emerging Modalities & DNA-Encoded Library Informatics: Develop and deploy specialized informatics workflows for non-traditional modalities (cyclic peptides, macrocycles) and DNA-Encoded Library platforms, including combinatorial enumeration, selection data triage, and hit prioritization
• Workflow & Algorithm Development: Design, validate, and implement scalable cheminformatics and machine learning pipelines for predictive property modeling, virtual screening, and chemical library triage
• Data Infrastructure & Tooling: Establish robust, automated computational tools and data pipelines that bridge internal chemical data platforms and modern modeling frameworks
• Scientific Presence & Mentorship: Maintain an active external scientific presence through publications, conference presentations, and community engagement, while mentoring junior staff, interns, and co-ops

Required Education

• Ph.D. (or close to completion) in Cheminformatics, Computational Chemistry, Chemistry, Computer Science, Bioinformatics, or a related quantitative discipline
• OR M.S. degree with 4+ years of relevant industry/research experience

Required Experience & Skills

• Demonstrated expertise in cheminformatics fundamentals (molecular representations, fingerprints, similarity search, tautomer enumeration, and conformer generation)
• Strong programming proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas, scikit-learn)
• Extensive hands-on experience with modern cheminformatics toolkits (e.g., RDKit, OpenEye Toolkits, or CDK)
• Experience developing and validating machine learning or statistical QSAR models applied to chemical or biological data
• Demonstrated track record of effective collaboration in multidisciplinary scientific teams
• Strong oral and written communication skills, evidenced by peer-reviewed publications or presentations

Preferred Experience

• Experience with computational design of cyclic peptides, macrocycles, or non-canonical peptide representations (e.g., HELM notation)
• Experience with DNA-Encoded Library analysis, combinatorial enumeration, or NGS selection data deconvolution
• Familiarity with molecular modeling and structure-based design tools (e.g., Schrödinger, MOE) to facilitate cross-talk with molecular modelers
• Experience deploying containerized workflows (Docker), version control (Git), and utilizing Linux/high-performance computing (HPC) environments