Data Analyst (Predictive Modeling)

Intone Networks

  • San Francisco, CA
  • 5 days ago

    Highlights

    Process, analyze, and model biomedical datasets including omics data, clinical trial data, real-world data (RWD), and in vitro/in vivo experimental data. You will support AI rapid prototyping and predictive modeling efforts for a DAISAE platform focused on drug safety risk prediction across the product lifecycle.

    Numbers & Facts

    LocationSan Francisco, CA

    Description

    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

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