Data Analyst Research I
Confirmed on the employer's own hiring board on Nov 6, 2026. First seen by Alion on Nov 4, 2026.
Position Summary
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 DT (Digital Tech) for formal validation, compliance, and production rollout.
* Cross-Functional Alignment: Collaborate with data scientists, safety scientists, and DT 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.
Pay Rate Range: $60-71/hr depending on experience