Merck & Co. is looking to advance high quality drug candidates into development by defining the non-clinical safety and selectivity of lead compounds through the Non-Clinical Drug Safety (NDS) team
Requirements
Proficiency in Python and associated data science packages including pandas, numpy, scipy, and sk-learn
Familiarity with pythonic frameworks for UI and dashboard creation such as Streamlet, Dash, and Plotly
Hands-on experience analyzing multiple data types including discrete, continuous, and time-series data
Familiarity with structured and un-structured data sources
Familiarity with statistics, discrete math, and probabilistic modeling
Familiarity with statistical learning methods, such as supervised and unsupervised modeling
Strong analytical skills
Responsibilities
Evaluate Lead Op candidates and preclinical toxicity of drug development candidates
Provide mechanistic understanding of drug-induced toxicity
Assess implications for human safety
Collaborate in animal model development, veterinary medical and animal care, and research facility management
Respond to regulatory questions in support of drug registration
Analyze multiple data types including discrete, continuous, and time-series data
Develop and apply statistical learning methods, such as supervised and unsupervised modeling
Other
Currently enrolled in a minimum of a BS/BA in applied math, computer science, chemistry, physics, computer engineering, biomedical engineering, or related disciplines
Available for a period of 10-12 weeks, beginning June 2026
