Predictive Modeling & AI/ML Scientist

Pharmaceutical Company; South San Francisco (CA); On-site; USD 96,000 - 193,000; Full time

Job summary

Pharmaceutical Company in South San Francisco seeks a contractor with expertise in AI prototyping, ML, and predictive modeling to advance the DAISAE platform and predictive analytics teams. The role focuses on agentic AI, shared data foundations, and drug safety risk prediction across the product lifecycle.

You will prototype AI tools, build predictive models from multimodal biomedical data, and contribute to ontologies and knowledge graphs while collaborating with data scientists, safety

Qualifications

• Advanced degree in a quantitative field with a strong research background.
• Experience building predictive models using biomedical data.
• Hands-on experience with AI prototyping and ML workflows.

Responsibilities

• Prototype and evaluate AI tools and agentic AI capabilities in a rapid, iterative process.
• Develop predictive analytics for drug safety risk assessment across product lifecycle.
• Collaborate to create ontologies, knowledge graphs, and shared data foundations.

Skills

Predictive modeling

Machine learning

AI prototyping

Software engineering

Agile

Communication

Education

MSc or PhD in Data Science

MSc or PhD in Computer Science

MSc or PhD in Computational Biology

MSc or PhD in Biostatistics

MSc or PhD in Epidemiology

Job description

We are seeking a contractor with expertise in AI prototyping, machine learning, and predictive modeling to support the DAISAE platform and predictive analytics teams. This role will focus on developing agentic AI capabilities, building shared data foundations such as ontologies and knowledge graphs, and advancing predictive models for drug safety risk prediction across the product lifecycle.

Key Responsibilities

• Rapidly prototype and evaluate AI tools, LLM-based solutions, and agentic AI capabilities, including ClientP tools and integrations for the DAISAE platform.
• Build and refine predictive models using multimodal biomedical datasets, including omics, in vitro/in vivo, clinical trial, real-world data (RWD), and spontaneous safety reports.
• Develop predictive analytics to support drug safety risk assessment from early molecule evaluation through clinical development and post-marketing.
• Contribute to shared data and technical architecture, including ontologies, knowledge graphs, and platform requirements.
• Collaborate with data scientists, safety scientists, and technical partners to develop reusable prototypes for subsequent validation and production rollout.
• Work in an agile environment to translate experimental findings into practical technical solutions aligned with business priorities.

Required Qualifications

• MSc or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative discipline.
• Strong hands-on experience in predictive modeling, machine learning, and AI prototyping.
• Experience developing agentic AI systems, LLM-based tools, and AI integrations.
• Experience working with biomedical datasets, such as omics, clinical trials, real-world data, or in vitro/in vivo data.
• Software engineering skills and an agile, rapid-prototyping mindset.
• Strong communication and cross-functional collaboration skills.

Preferred Qualifications

• Experience in pharmacovigilance, drug safety, toxicology, or quantitative risk management.
• Experience with ontologies, knowledge graphs, and shared data platforms.
• Ability to adapt quickly to emerging AI frameworks and technologies.