We are seeking a Data Analyst (Predictive Modeling) for a 6-month contract role based in San Francisco, California, with remote options available. You will support AI rapid prototyping and predictive modeling efforts for a DAISAE platform focused on drug safety risk prediction across the product lifecycle. Responsibilities Develop and prototype predictive models and machine learning solutions for drug safety applications Design and implement agentic AI systems, large language model (LLM) tools, and MCP (Model Context Protocol) tools Process, analyze, and model biomedical datasets including omics data, clinical trial data, real-world data (RWD), and in vitro/in vivo experimental data Collaborate with cross-functional teams using Agile methodologies Support rapid prototyping cycles and iterative development of AI-driven safety risk prediction capabilities Qualifications Required Master's degree or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative field 3+ years of hands-on experience developing predictive models, machine learning solutions, and AI prototyping 3+ years of experience developing agentic AI systems, LLM tools, and MCP tools 3+ years of proficiency in handling biomedical datasets (omics, clinical trials, RWD, or in vitro/in vivo data) 2+ years of experience working with Agile methodologies Preferred 5+ years of background in pharmacovigilance, drug safety, toxicology, or quantitative risk management