Computational Scientist (Medicinal Chemistry)

About the Company

Axiom is building a compounding ecosystem to replace animal testing and reshape how clinical trials are run. By building world-class datasets and advancing ML research, Axiom creates an agentic infrastructure that helps pharma companies predict human drug outcomes more accurately than traditional animal models.

Responsibilities

• Lead the analysis of model outputs across chemical series, targets, modalities, and clinical toxicity endpoints
• Identify model performance gaps and interpret what failures reveal about chemistry, biology, or exposure
• Work with ML researchers to improve models predicting human toxicity based on chemical structure and biological response
• Clean, curate, and structure large-scale chemical datasets, including ADME properties and clinical outcomes
• Use medicinal chemistry intuition to interpret structure–toxicity relationships
• Partner with pharma and biotech customers to interpret model outputs and influence drug program decisions
• Help design new experimental and molecular datasets based on model failures and customer needs

Requirements

• Advanced degree in chemistry, computational chemistry, cheminformatics, medicinal chemistry, or chemical biology
• Deep understanding of drug discovery workflows from hit discovery to candidate selection
• Ability to reason about potency, selectivity, physicochemical properties, ADME, PK, and clinical translatability
• Experience analyzing large chemical datasets using data science and biological reasoning
• Strong communication skills to earn the trust of senior drug hunters and pharma customers

Preferred Qualifications

• Proficiency in Python, Pandas, NumPy, SciPy, scikit-learn, and Jupyter notebooks
• Experience with RDKit, Datamol, DeepChem, or related cheminformatics tooling
• Expertise in chemical structure processing, scaffold analysis, and molecular fingerprints
• Experience with QSAR, molecular property prediction, or toxicity prediction
• Knowledge of SQL and cloud data workflows
• Experience with drug discovery datasets involving targets, assays, and toxicology