About the role
Eikon Therapeutics is a new biopharmaceutical company employing revolutionary technology at the intersection of chemistry, engineering, computation, and biology to discover novel treatments for life-threatening diseases. Eikon’s discovery platform is built on groundbreaking innovations from its founders (Nobel Prize, 2014), culminating in the creation of microscopes which enable real time, molecular-resolution measurements of protein movement in living cells, thereby unlocking otherwise intractable classes of proteins as drug targets. Position We are seeking an accomplished and forward-thinking Senior Data Science, Biology to join our dynamic team. As a Senior Data Science, Biology, you will lead the analysis and interpretation of complex biological data, leveraging advanced computational techniques to drive critical insights for our biotech research and development initiatives. About You The ideal candidate is passionate about harnessing the latest advances in AI including large language models (LLMs), multi-agent systems, and retrieval-augmented generation (RAG) to unlock insights from biological data. They bring deep proficiency in Python and a track record of building agentic workflows that automate complex, multi-step analytical tasks. They have extensive experience with genomics, transcriptomics, proteomics, and multi-omics data, and are excited to apply modern AI paradigms to these domains. Their strong foundation in bioinformatics is complemented by hands-on experience with AI frameworks and tools, allowing them to bridge the gap between biological science and cutting-edge AI engineering. What You’ll Do Lead and collaborate with interdisciplinary teams to analyze and interpret diverse biological data sets, including genomics, proteomics, and multi-omics data. Apply cutting-edge AI and machine learning techniques including LLMs, deep learning, and foundation models to extract meaningful patterns and actionable insights from complex biological data. Design and implement agentic AI workflows that orchestrate multiple AI models and tools to autonomously analyze biological pathways, interactions, and phenomena. Contribute to experimental design, generating high-quality data for analysis, modeling, and hypothesis testing. Integrate and harmonize disparate data sources to provide comprehensive insights and support research projects. Develop and optimize agentic AI pipelines that automate multi-step biological data analysis tasks, enabling reproducible, high-throughput processing at scale. Communicate technical findings and insights effectively to both technical and non-technical stakeholders. Stay at the forefront of AI research including advances in LLMs, agentic systems, and multimodal models and rapidly translate these innovations into biological data analysis applications.