2026 Future Talent Program – Nonclinical Drug Safety Data Scientist – Intern Full-time

Internship Opportunity In Research And Development Division

The Future Talent Program features internships that last up to 12 weeks and will include one or more projects. These opportunities in our Research and Development Division can provide you with great development and a chance to see if we are the right company for your long-term goals.

Non-Clinical Drug Safety (NDS) helps advance high quality drug candidates into development by defining the non-clinical safety and selectivity of lead compounds. Non-Clinical Drug Safety employees evaluate Lead Op candidates and preclinical toxicity of drug development candidates, provide mechanistic understanding of drug-induced toxicity, and assess implications for human safety. Non-Clinical Drug Safety provides collaborative research in animal model development, veterinary medical and animal care, and research facility management. Non-Clinical Drug Safety also responds to regulatory questions in support of drug registration.

Our ability to excel depends on the integrity, knowledge, imagination, skill, diversity and teamwork of people like you. To this end, we strive to create an environment of mutual respect, encouragement and teamwork. As part of our global team, you'll have the opportunity to collaborate with talented and dedicated colleagues while developing and expanding your career.

Locations: West Point, PA / Boston, MA

Education: Candidates should currently be enrolled in a minimum of a BS/BA in applied math, computer science, chemistry, physics, computer engineering, biomedical engineering, or related disciplines.

Required Experience: Must be available for a period of 10-12 weeks, beginning June 2026.

Preferred Experience/Skills: Should have a G.P.A of 3.0 or higher. Should have strong analytical and communication skills. Should have demonstrated ability to learn new technologies. Should have proficiency in Python and associated data science packages including pandas, numpy, scipy, and sk-learn. Should have familiarity with pythonic frameworks for UI and dashboard creation such as Streamlet, Dash, and Plotly. Should have hands-on experience analyzing multiple data types including discrete, continuous, and time-series data. Should have familiarity with structured and un-structured data sources. Should have familiarity with statistics, discrete math, and probabilistic modeling a plus. Should have familiarity with statistical learning methods, such as supervised and unsupervised modeling.

Salary range: $39,600.00-$105,500.00 USD