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# Data Scientist

- **Company:** Sanofi
- **Location:** Cambridge, MA, United States
- **Salary:** $97,760.0 - $124,800.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Bioinformatics, Computer Programming, Python (Programming Language), Language Modeling, Tensorflow, Pytorch, Transfer Learning, Large Language Models, Deep Learning, Kubernetes, Information Technology, AlphaFold
- **Published:** October 17, 2026
- **Apply:** https://startup.jobs/2027-spring-co-op-biologics-design-and-ai-cambridge-ma-2148-sanofi-aventis-de-colom-10495597

## About the Role

* Currently pursuing a Master's or PhD degree in Computer Science, Data Science, Computational Biology, Bioinformatics, Bioengineering, or related field with plans to graduate by Spring 2027 (or 2028).
 * Must be permanently authorized to work in the U.S. and not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future. Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the Internal requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.
 * Must be enrolled in an accredited college or university throughout the duration of the co-op/internship.
 * Must be able to relocate to the office location and work 40hrs/week, Monday to Friday for the full duration of the co-op/internship., * Previous academic projects or industry experience demonstrating the application of NLP, LLMs, or agentic workflows to complex, ideally scientific, problems.
 * Familiarity with biological data, specifically protein sequences and 3D structures.
 * Basic domain knowledge in immunology, structural biology, or biophysics.
 * Strong programming skills in Python and standard data science libraries.
 * Hands-on experience with LLM fine-tuning methodologies and orchestration frameworks.
 * Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
 * Experience using state-of-the-art AI tools for biology (e.g., Protein LLMs, AlphaFold, Rosetta).
 * Excellent problem-solving communication skills, with a passion for working at the intersection of generative AI and healthcare.
 * Fluent in English.

## Description

* LLM Fine-Tuning & Cross-Modal Adaptation: Fine-tune conversational, natural language LLMs to directly interface with and reason over data from specialized protein prediction models. Using parameter-efficient techniques (e.g., LoRA, PEFT), you will adapt these human-language models to comprehend protein sequences, structural embeddings, and biophysical constraints. By bridging the gap between human-like generative AI reasoning and rigorous structural biology, you will build hybrid architectures designed to significantly enhance the accuracy of critical antibody and nanobody property predictions, such as binding affinity and thermal stability.
 * Collaboration & Reporting: Partner closely with experimental protein engineers and computational biologists to understand biological constraints, define the agent's objectives, and validate model predictions, ultimately presenting your methodologies, insights, and model performance to cross-functional R&D teams at the conclusion of the spring term., * Stretch your skills through apprenticeships, internships, graduate programs, and international experiences that grow with you.
 * Learn from inspiring mentors and collaborative teams while contributing to real projects that shape the future of healthcare.
 * Build your future with access to the latest tools, digital innovation, and continuous learning that keep you ahead of the curve.