Data Scientist - Antibody Design

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Lilly’s Biotechnology Discovery Research (BioTDR) organization has a track record for delivering novel biotherapeutic medicines advanced into clinical research in key areas of unmet medical needs, across a variety of therapeutic areas. Integrating biology with innovative scientific capabilities in protein discovery, engineering and computational sciences, we are committed to delivering next wave of biomedicines. We are seeking a passionate data scientist to join our high-energy team at the forefront of computational research to bolster antibody discovery and engineering efficiency. This position lies at the cross-section of computational science, antibody discovery and engineering, automation, protein bioscience, and Information technology, is located at the Lilly Biotechnology Center in San Diego. Working in this collaborative environment with access to cutting-edge technologies and resources, you play an active role in the development and deployment of new antibody design algorithms, in silico predictive models, and computational pipeline to accelerate antibody discovery impacting multiple disease areas. Primary Responsibilities: Develop, implement, and maintain computational tools for analyzing large-scale biological datasets related to antibody sequences, structures, and functions Assist in developing predictive models for predicting antibody properties such as affinity or specificity using Python libraries like scikit-learn, Pandas or PyTorch Work closely with senior scientists to integrate AI/ML approaches into existing workflows for antibody engineering and de novo Ab design Identify patterns in biological data to inform antibody selection and design strategies Collaborate with cross-functional teams to design experiments, analyze data from high-throughput assays Participate in the development of databases and data visualization tools Basic Qualifications Bachelor's or Master's degree in Computer Science, Bioinformatics, Biostatistics, Mathematics, or a related field with strong programming skills Additional Skills and Preferences At least 2 years of experience working with large datasets (genomics/proteomics) using languages such as Python/R/SQL Proficiency in machine learning frameworks like PyTorch/TensorFlow/Keras; familiarity with deep learning concepts such as Large language model or diffusion model is preferred Familiarity with bioinformatics tools such as BLAST /BioPython Experience of protein structure prediction software (e.g., AlphaFold) is a plus Experience of sequence-based and physics-based computational methods, including MOE, Schrodinger LiveDesign, Rossetta, other visualization and analysis software (e.g., PyMOL) Experience with cloud computing platforms and high-performance computing environments Ability to work productively and collaboratively in an interdisciplinary team environment Additional Information Location: San Diego, CA

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