Principal Scientist, Biology-Discovery Full-time NEW

Principal Scientist

The Screening & Compound Profiling group within the Quantitative Biosciences Department is seeking a Principal Scientist with deep expertise in applied quantitative pharmacology and/or biochemistry to join our Research Laboratories in Rahway, NJ. This role will provide senior-level expertise at the interface of in vitro pharmacology and quantitative modeling. The successful candidate will serve as a scientific resource across the broader research organization, contributing rigorous pharmacological analysis across programs and delivering mechanistic insight to drug discovery decisions spanning target classes, modalities, and therapeutic areas. The primary responsibilities of this role will be to develop, apply, and communicate quantitative data models that elucidate molecular mechanisms of action, support translational profiling of compound activities, and guide molecular optimization.

Responsibilities:

• Provide quantitative analysis and consultation to drug discovery project teams across the network, either as an embedded team member or as an advisory resource
• Develop and apply mechanistic and empirical models to characterize compound activity and inform structure-activity relationships
• Translate pharmacological data into actionable recommendations for medicinal chemistry, biology, and translational colleagues
• Mentor junior scientists in analytical methods, modeling approaches, and effective data communication
• Represent Screening & Compound Profiling in cross-functional and cross-site settings, contributing pharmacological perspective to broader strategic discussions
• Foster a collaborative, inclusive team environment that supports scientific rigor and professional growth

Education Requirement: Ph.D. in pharmacology, biochemistry, biophysics, or a closely related discipline with 10 years of relevant experience.

Required Experience and Skills:

• Extensive drug discovery experience, preferably in an industry setting, with demonstrated impact across multiple programs and/or therapeutic areas
• Deep expertise in quantitative pharmacological frameworks including dose-response analysis, enzyme kinetics, receptor binding theory, and mechanistic modeling of drug action
• Strong mathematical foundation in calculus, ordinary differential equations, and applied statistics as used in pharmacological modeling and quantitative data analysis
• Exceptional communication skills — able to construct clear, data-driven narratives and calibrate delivery to diverse audiences without sacrificing scientific rigor

Preferred Experience and Skills:

• Proficiency in scientific computing (Python and/or R) for model fitting, simulation, and development of analytical tools
• Familiarity with contemporary hit-finding and screening approaches including affinity-oriented techniques (DNA-encoded libraries, mRNA display), high-throughput screening (binding and cellular functional assays, biochemical functional readouts), and assay development, miniaturization, optimization, and validation for screening
• Familiarity with molecular and cell biology, physiology, and contemporary experimental approaches to evaluate experimental perturbation of biological processes including high-content imaging, transcriptomics (RNA-seq, DRUG-seq), proteomics, and mass spectrometry, with sufficient quantitative literacy to interpret and contextualize results

Required Skills:

• Adaptability
• Biochemical Assays
• Cell-Based Assays
• Communication
• Compound Screening
• Data Analysis
• Detail-Oriented
• Enzymology
• Ethical Compliance
• In Vitro Pharmacology
• Leading Project Teams
• Mathematics
• Mathematics Modeling
• Mechanism of Action
• Mentor Coaching
• Molecular Profiling
• Numerical Modeling
• Persuasion
• Professional Networking
• Quantitative Reasoning
• Simulation Models
• Statistics
• Systems Biology

Preferred Skills:

• Adaptability
• Biochemical Assays
• Cell-Based Assays
• Communication
• Compound Screening
• Data Analysis
• Detail-Oriented
• Enzymology
• Ethical Compliance
• In Vitro Pharmacology
• Leading Project Teams
• Mathematics
• Mathematics Modeling
• Mechanism of Action
• Mentor Coaching
• Molecular Profiling
• Numerical Modeling
• Persuasion
• Professional Networking
• Quantitative Reasoning
• Simulation Models
• Statistics
• Systems Biology