Senior Scientist: Cheminformatics & Computational Chemistry

Hybrid work schedule: Remote candidates may be considered on a case-by-case basis.

Job Summary:

• We are seeking a highly motivated Cheminformatics Scientist to design, evaluate, and build end-to-end small molecule computational workflows within the client platform.
• This role requires strong hands-on expertise in state-of-the-art computational methods across the drug discovery pipeline, from virtual screening to lead optimization.
• You will work at the intersection of cheminformatics, physics-based modeling, and machine learning, partnering closely with client software engineering and ML teams to deliver scalable, production-grade workflows.
• This is a high-impact contract role, where you will be expected to independently evaluate tools, make build-vs-buy decisions, and deliver robust workflow solutions.

Key Responsibilities:

End-to-End Workflow Development:

• Design and implement workflows spanning:
  • Virtual screening (ligand-based and structure-based).
  • Hit identification and hit expansion.
  • Hit-to-lead selection.
  • Lead optimization.

Method Development & Application:

• Apply and integrate core computational chemistry and cheminformatics methods, including:
  • Ultra-large library search:
    • Substructure search.
    • Fingerprint and embedding-based similarity search.
    • Shape and pharmacophore-based screening.
  • Molecular enumeration:
    • Reaction-based enumeration.
    • Fragment-based design and expansion.
  • Ligand-based modeling:
    • QSAR, similarity, clustering, active learning loops.
  • Structure-based modeling:
    • Docking, rescoring, pose prediction, structure-aware search.
  • Physics-based methods:
    • Molecular dynamics (MD).
    • Free energy perturbation (FEP) and related approaches.

Cross-functional Collaboration:

• Partner with:
  • Machine Learning teams to integrate predictive and generative models.
  • Software Engineering teams to productionize workflows and ensure scalability.
  • Scientific stakeholders to align workflows with drug discovery needs.

Required Qualifications:

• PhD or MS in Cheminformatics, Computational Chemistry, Medicinal Chemistry, or related field.
• Strong understanding of small molecule drug discovery workflows.
• Demonstrated expertise in:
  • Substructure and similarity search (fingerprints, graph-based, embedding-based).
  • Shape and pharmacophore searching.
  • Reaction-based and fragment-based enumeration.
  • Docking and structure-based design.
  • QSAR and ligand-based modeling.
  • Active learning and iterative design strategies.
  • Physics-based simulations (e.g., MD, FEP).
• Hands-on experience with tools such as:
  • RDKit, OpenEye, or equivalent.
  • Docking platforms (e.g., Glide, AutoDock, GOLD).
• Strong programming skills in Python.

Preferred Qualifications:

• Experience working with ultra-large chemical libraries (e.g., Enamine REAL, WuXi Galaxy).
• Familiarity with generative chemistry approaches (SMILES-, graph-, or diffusion-based models).
• Experience integrating ML models into production workflows.
• Experience with workflow orchestration tools (e.g., Airflow, Nextflow).