Senior Scientist: Cheminformatics and Computational Chemistry

Job Title: Senior Scientist: Cheminformatics and Computational Chemistry

Job Location: San Francisco, CA

Job Type: Contract

Job Overview:

Pay Range: $85.19hr - $90.19hr

Requirement/Must Have:

• PhD or MS in Cheminformatics, Computational Chemistry, Medicinal Chemistry, or a related field.
• Strong understanding of small molecule drug discovery workflows.
• Expertise in substructure and similarity search methods, including fingerprint, graph-based, and embedding-based approaches.
• Experience with shape and pharmacophore-based searching.
• Experience with reaction-based and fragment-based molecular enumeration.
• Experience with docking and structure-based design.
• Experience with QSAR and ligand-based modeling.
• Experience with active learning and iterative design strategies.
• Experience with physics-based simulations such as molecular dynamics and free energy perturbation.
• Hands-on experience with cheminformatics tools such as RDKit, OpenEye, or equivalent.
• Experience with docking platforms such as Glide, AutoDock, or GOLD.
• Strong programming skills in Python.
• Ability to design and implement end-to-end computational workflows.
• Strong analytical, problem-solving, and communication skills.

Experience:

• Experience designing and implementing workflows across the drug discovery pipeline.
• Experience in virtual screening, hit identification, hit expansion, and lead optimization.
• Experience integrating computational chemistry, cheminformatics, and machine learning approaches.
• Experience collaborating with machine learning and software engineering teams.
• Experience building scalable and production-grade workflow solutions.
• Experience evaluating tools and making build-versus-buy decisions.

Responsibilities:

• Design and implement end-to-end workflows for small molecule drug discovery, including virtual screening, hit identification, hit expansion, hit-to-lead selection, and lead optimization.
• Apply and integrate computational chemistry and cheminformatics methods such as substructure search, similarity search, pharmacophore modeling, and molecular enumeration.
• Perform ligand-based modeling, including QSAR, similarity analysis, clustering, and active learning workflows.
• Perform structure-based modeling, including docking, rescoring, pose prediction, and structure-aware search.
• Apply physics-based methods such as molecular dynamics and free energy perturbation.
• Collaborate with machine learning teams to integrate predictive and generative models into workflows.
• Work with software engineering teams to productionize workflows and ensure scalability.
• Partner with scientific stakeholders to align computational workflows with drug discovery objectives.
• Evaluate tools and technologies and make informed build-versus-buy decisions.

Should Have:

• Experience working with ultra-large chemical libraries preferred.
• Familiarity with generative chemistry approaches such as SMILES-, graph-, or diffusion-based models preferred.
• Experience integrating machine learning models into production workflows preferred.
• Experience with workflow orchestration tools such as Airflow or Nextflow preferred.

Skills:

• Cheminformatics.
• Computational chemistry.
• Drug discovery workflows.
• Virtual screening.
• Molecular modeling.
• QSAR modeling.
• Structure-based design.
• Ligand-based modeling.
• Molecular dynamics.
• Free energy perturbation.
• Python programming.
• RDKit or equivalent tools.
• Docking platforms.
• Workflow development.
• Machine learning integration.
• Data analysis.
• Cross-functional collaboration.