Predictive Modeling Contractor

Spectraforce Technologies; South San Francisco (CA); Remote; USD 96,000 - 165,000; Part time

Job summary

Spectraforce Technologies, Inc. seeks a Predictive Modeling Contractor to advance AI prototyping and predictive modeling for the DAISAE platform.

The role emphasizes rapid tool evaluation, ontology and knowledge-graph foundations, and multi-modal data integration to support drug safety risk prediction across development stages. Candidates should hold MSc/PhD in quantitative fields and demonstrate experience with agentic AI, LLM tooling, and biomedical datasets.

Qualifications

• Advanced degree in data science, CS, computational biology, or related field.
• Strong background in predictive modeling, ML, and AI prototyping.
• Experience developing agentic AI systems and MCP/LLM tooling.
• Experience handling omics, clinical trials, RWD, or biomedical data.
• Agile prototyping mindset with data-science oriented software engineering.

Responsibilities

• AI prototyping and tool development for MCP and DAISAE.
• Build and refine predictive models using diverse biomedical datasets.
• Translate feasibility findings into architectural design and platform needs.
• Prototype reusable capabilities before transitioning to validation and production.
• Collaborate with data scientists and safety scientists to align with priorities.

Skills

Predictive modeling

Machine learning

AI prototyping

Agentic AI systems

LLM tools

MCP tools

Biomedical datasets

Agile prototyping

Education

MSc or PhD in Data Science/CS/Bioinformatics

Tools

LLM tools

MCP tools

Job description

Title: Predictive Modeling Contractor

Location: 14 months

Duration: South San Francisco, CA 94080 (open to remote as well)

Description

We are seeking a contractor with a background combining AI rapid prototyping and Predictive Modeling to support the DAISAE platform and predictive analytics subteams within the RDE 9 program. This role focuses on co-developing shared data and technical foundations (e.g. Ontologies, Knowledge Graphs), prototyping agentic AI capabilities, and advancing predictive models for drug safety risk prediction across the product lifecycle.

Key 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's 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.

Qualifications & Experience

• Education: 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.