Clinical Data Analyst_Research I_CO - Predictive Modeling

IT Engagements, Inc.; South San Francisco (CA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

IT Engagements, Inc. is seeking a Data Analyst_Research I_CO - Predictive Modeling for a contract engagement in San Francisco, CA (remote option). The role focuses on AI rapid prototyping and predictive modeling to advance the DAISAE platform.

The role involves co-developing shared data foundations and prototyping agentic AI capabilities, working with data scientists and risk teams to enable drug safety risk prediction across the product lifecycle.

Qualifications

• Strong background in predictive modeling and AI prototyping.
• Experience with multi-modal biomedical datasets.
• Familiarity with data governance and agile prototyping.

Responsibilities

• Prototype AI tools and agentic capabilities for DAISAE.
• Build and refine predictive models across diverse datasets.
• Translate prototype findings into architectural design.
• Collaborate with data scientists and RDT partners in an agile setup.
• Align technical work with business priorities.

Skills

AI prototyping

Predictive modeling

Agentic AI systems

Biomedical datasets

Education

MSc or PhD in Data Science or related quantitative field

Tools

LLM tools

MCP tools

Job description

Hi, Greetings from IT Engagements! IT Engagements is a global staff augmentation firm providing a wide-range of talent on-demand and total workforce solutions. We have an immediate opening for the below position with one of our premium clients.

Role

Data Analyst_Research I_CO - Predictive Modeling

Location

San Francisco, CA/Remote

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 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.

Education

MSc or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative field.

Qualifications & Experience

• 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.