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Drug Discovery Scientist; Medicinal Chemistry​/Pharmacology | Remote

Remote / Online - Candidates ideally in
West Jordan, Salt Lake County, Utah, 84081, USA
Listing for: Crossing Hurdles
Remote/Work from Home position
Listed on 2026-06-02
Job specializations:
  • Research/Development
    Data Scientist
  • IT/Tech
    Data Analyst, Data Scientist, Data Science Manager, Data Security
Salary/Wage Range or Industry Benchmark: 70 - 100 USD Hourly USD 70.00 100.00 HOUR
Job Description & How to Apply Below
Position: Drug Discovery Scientist (Medicinal Chemistry / Pharmacology) | Remote

Position: Drug hunters (chemists) or toxicologists

Type: Hourly contract

Compensation: $70-$100 per hour

Location: Remote

Commitment: 10–40 hours/week

Role Responsibilities

  • Review and annotate datasets related to drug discovery, pharmacology, and safety biology
  • Interpret experimental outputs from target biology studies, biochemical assays, cellular models, and safety screens
  • Analyze relationships between compound structure, potency, selectivity, exposure, and toxicity signals
  • Identify mechanistic explanations behind efficacy or toxicity findings across discovery experiments
  • Distinguish meaningful biological signal from experimental artifacts, assay interference, or model limitations
  • Audit annotated datasets for biological, pharmacological, and safety accuracy
  • Validate structure–activity relationships, target engagement logic, and pharmacokinetic interpretations
  • Evaluate AI-generated reasoning on drug mechanism, toxicity risk, and safety margins
  • Ensure correct interpretation of dose-response relationships, exposure margins, and translational relevance
  • Contribute to annotation guidelines for drug discovery workflows, SAR, pharmacokinetics, toxicity mechanisms, and translational biology
  • Provide expertise on balancing potency, selectivity, safety, and develop ability
  • Advise on classification of toxicity findings, safety signals, and risk assessment frameworks
  • Review AI-generated reasoning on drug mechanism, target biology, toxicity, and pharmacokinetics
  • Assess whether conclusions logically follow from experimental evidence and biological context
  • Provide structured feedback to improve scientific rigor and reasoning in model outputs
  • Contribute to scientific standards documentation and training materials
  • Help define gold‑standard examples of drug discovery reasoning and toxicity interpretation
  • Support calibration workflows across pharmacology, toxicology, and translational biology

Requirements

  • Advanced degree such as PhD, Pharm

    D, DVM, MD, or MS with significant industry experience in medicinal chemistry, pharmacology, toxicology, chemical biology, molecular biology, pharmaceutical sciences, or biochemistry
  • Hands‑on experience in drug discovery or safety assessment including target validation through lead optimization
  • Experience in structure–activity relationship analysis
  • Experience in pharmacokinetics and ADME interpretation
  • Experience in toxicology and safety pharmacology studies
  • Experience interpreting in vitro and in vivo experimental data
  • Strong expertise in target biology and mechanism‑of‑action reasoning
  • Understanding of dose‑response relationships and exposure margins
  • Ability to interpret translational relevance between preclinical and clinical findings
  • Knowledge of toxicity mechanisms such as liver toxicity, cardiovascular liabilities, genotoxicity, or reproductive toxicity
  • Ability to evaluate safety findings for risk and program impact
  • Experience reviewing primary experimental data and study reports
  • Exceptional attention to scientific accuracy and mechanistic reasoning
  • Experience in pharmaceutical or biotechnology drug discovery teams
  • Background in lead optimization, translational biology, or nonclinical safety
  • Familiarity with DMPK workflows, safety biomarkers, and regulatory toxicology considerations
  • Experience contributing to cross‑functional discovery teams
  • Exposure to AI or ML tools applied to biomedical research
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