Principal Scientist, Biology-Discovery

MSD•Rahway, NJ

3d•Hybrid

About The Position

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. The ideal candidate will combine authoritative command of foundational concepts in drug action rooted in biochemistry, enzymology, transporter/channel biology, or a related discipline with strong mathematical fluency and the ability to address complex pharmacological challenges in a collaborative, cross-functional environment. This individual will materially strengthen local lead-finding capabilities while partnering with teams across the research network to advance our discovery pipeline.

Requirements

Ph.D. in pharmacology, biochemistry, biophysics, or a closely related discipline with 10 years of relevant experience.
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
Established scientific reputation evidenced by publications, presentations, or recognized contributions to the field
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

Nice To Haves

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

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