2026 Future Talent Program - Computer Scientist - Co-Op

Merck•Upper Gwynedd Township, PA

About The Position

The Future Talent Program features Cooperative (Co-op) education that lasts up to 6 months 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. Nonclinical Drug Safety helps advance high-quality drug candidates into development by defining the nonclinical safety and selectivity of lead compounds. Nonclinical Drug Safety employees evaluate Lead Op candidates and preclinical toxicity of drug development candidates, providing a mechanistic understanding of drug-induced toxicity and assessing implications for human safety. Nonclinical Drug Safety provides collaborative research in animal model development, veterinary medical and animal care, and research facility management. Nonclinical Drug Safety also responds to regulatory questions in support of drug registration. The Digital Operations and Innovation team within Nonclinical Drug Safety Operations comprises a talented group of data scientists dedicated to leveraging scientific and operational data to reduce administrative burden, improve the findability and accessibility of data, and discover and implement innovative applications of AI to modernize and advance our business. Position Overview: We seek a talented and motivated Co-op Computer Scientist to join our team for a six-month role. This position will contribute to the development of a web-based application that will enable our scientific and business leaders to retrieve critical scientific and operational data, surface similarities and patterns in the data, and generate natural language summaries of the structured and unstructured data being displayed. The ideal candidate will actively participate in regular sprints to develop and refine features in the application, propose new ideas and creative solutions to combine operational and scientific data, and consider the UI and UX impact of design choices. Additionally, there will be opportunities to contribute to the construction and evaluation of unsupervised clustering models and LLMs for integration into the solution. In this role, you will be a valued contributor to a visible and necessary effort aimed at modernizing how nonclinical safety fulfills its critical role in the development of safe medicines for our patients. Your work will help produce stable, reliable, and user-friendly tools that bring data and insight to the scientists at the cutting edge of our field. The ideal candidate will have experience with web frameworks such as DASH and working with both structured and unstructured data. Strong Python coding and documentation skills are essential. Familiarity with AWS services (Redshift, S3, EC2), GitHub Actions, LLMs, and vector databases are an additional advantage.

Requirements

Must be currently pursuing a bachelor's or master's degree in computer science, Data Science, Software Engineering, or a related field
Must have strong proficiency in Python programming and code documentation
Must have experience working with structured and unstructured data
Must have excellent problem-solving skills and attention to detail
Must have effective communication and teamwork abilities

Nice To Haves

Experience with web frameworks (DASH, Streamlit, Flask, or similar)
Familiarity with version control using Git/GitHub
Experience with AWS services (Redshift, S3, EC2) or other cloud platforms
Exposure to machine learning concepts, LLMs, or vector databases
Previous co-op or internship experience in software development or data science

Responsibilities

Participate in agile sprints to develop and refine dashboard features based on user feedback from scientists and business leaders
Build data pipelines in Python to integrate structured and unstructured data sources into the application.
Design and implement interactive visualizations using DASH to surface patterns and insights in operational and scientific data
Contribute to code reviews and maintain documentation using GitHub
Collaborate with the team to evaluate and integrate ML models (clustering, LLMs) into the dashboard application