Predictive Modeling Contractor (RDE 9 / DAISAE)

Iconma LLC

  • South San Francisco, CA
  • 11 days ago

    Highlights

    Predictive Modeling: Build and refine predictive models using multi-modal datasets (including in vitro, in vivo, omics, clinical trial data, real-world data (RWD), and spontaneous safety reports) to enable risk prediction from early molecule-level evaluation to late-stage and post-marketing patient safety. Responsibilities: AI Prototyping & MCP Tool Development: Rapidly explore, evaluate, and prototype emerging AI tools and agentic capabilities, specifically developing MCP tools and AI agent integrations for DAISAE.

    Numbers & Facts

    LocationSouth San Francisco, CA

    Description

    Our Client, a Biotech company, is looking for a Predictive Modeling Contractor (RDE 9 / DAISAE) for their South San Francisco, CA location.

    Responsibilities:

    • AI Prototyping & MCP Tool Development: Rapidly explore, evaluate, and prototype emerging AI tools and agentic capabilities, specifically developing MCP tools and AI agent integrations for DAISAE.
    • Predictive Modeling: Build and refine predictive models using multi-modal datasets (including in vitro, in vivo, omics, clinical trial data, real-world data (RWD), and spontaneous safety reports) to enable risk prediction from early molecule-level evaluation to late-stage and post-marketing patient safety.
    • Architecture & Platform Design: Translate feasibility findings and prototype evaluations into concrete architectural design and platform requirements for shared data and technical foundations.
    • Co-Development & Governance Collaboration: Work in an agile way to prototype reusable technical capabilities before transitioning components to RDT (Client Digital Tech) for formal validation, compliance, and production rollout.
    • Cross-Functional Alignment: Collaborate with data scientists, safety scientists, and RDT technical partners to ensure technical execution aligns with business priorities.

    Requirements:

    • MSc or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative field.
    • Technical Expertise:
    • Strong expertise in predictive modeling, machine learning, and AI prototyping.
    • Hands-on experience developing agentic AI systems, LLM tools, and MCP tools.
    • Proficiency in handling biomedical datasets (omics, clinical trials, RWD, or in vitro/in vivo data).
    • Agile prototyping mindset with software engineering skills tailored for data science.
    • Domain Knowledge:
    • Background in pharmacovigilance, drug safety, toxicology, or quantitative risk management is highly desirable.
    • Soft Skills:
    • AI native" approach to problem-solving with adaptability to fast-moving frameworks.
    • Proactive attitude and strong communication skills suitable for global matrix team settings.

    Why Should You Apply?

    • Health Benefits
    • Referral Program
    • Excellent growth and advancement opportunities

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