AI Modeling Scientist

Employment Type: W2 Contract – 13 Months with Possibility for Extensions

Pay Rate: $61.00–$71.07/hour – Based on experience

Work Model: South San Francisco Preferred;
Remote May Be Considered for Qualified Candidates

Benefits: Medical, Dental, Vision, and Life Insurance

Note:
This is a W2 only role — C2C and C2H will not be considered.

BEPC is seeking an experienced AI Modeling Scientist to support our client's predictive analytics and artificial intelligence initiatives in the pharmaceutical and biotechnology industry.

This position focuses on predictive modeling, machine learning, agentic AI development, and biomedical data analysis to advance drug safety risk prediction throughout the pharmaceutical product lifecycle.

The ideal candidate has an MSc or PhD in a quantitative discipline, hands‑on experience developing LLM-based AI agents and Model Context Protocol (MCP) tools, and expertise in building predictive models using complex biomedical datasets.

• Develop and optimize predictive models and machine learning solutions for drug safety and risk assessment.
• Analyze multimodal biomedical datasets, including omics, clinical trial data, real‑world data (RWD), in vitro/in vivo data, and safety reports.
• Design and prototype agentic AI systems, LLM integrations, and Model Context Protocol (MCP) tools.
• Evaluate emerging AI technologies and develop rapid prototypes to assess technical feasibility.
• Support drug safety risk prediction from early research through clinical development and post‑marketing surveillance.
• Develop reusable data and AI capabilities, including ontologies and knowledge graphs.
• Translate prototype findings into technical architecture, platform requirements, and scalable solutions.
• Collaborate with data scientists, safety scientists, software engineers, and technical stakeholders.
• Support agile development, experimentation, and iterative improvement of AI capabilities.
• Prepare prototypes and technical documentation for transition to formal validation, compliance, and production implementation.

• Master's degree (MSc) or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative field.
• Strong experience in predictive modeling, machine learning, and AI rapid prototyping.
• Hands‑on experience developing agentic AI systems, Large Language Model (LLM) tools, and Model Context Protocol (MCP) integrations.
• Experience analyzing biomedical datasets, such as omics, clinical trial, real‑world, or in vitro/in vivo data.
• Strong software engineering and prototyping skills applied to data science workflows.
• Ability to evaluate emerging AI frameworks and translate technical findings into practical solutions.
• Understanding of data architecture, reusable technical capabilities, and scalable AI platforms.
• Strong analytical, problem‑solving, and communication skills.
• Ability to collaborate effectively within global, cross-functional, and matrixed teams
  .
• Self‑motivated, adaptable, and comfortable working in a fast‑paced, evolving AI environment.

• Experience in pharmacovigilance, drug safety, toxicology, or quantitative risk management.
• Experience developing predictive models for pharmaceutical research, clinical development, or patient safety.
• Familiarity with knowledge graphs, ontologies, and biomedical data integration.
• Experience transitioning AI prototypes into validated or production‑ready systems.
• Background in biotechnology, pharmaceutical research, or regulated healthcare environments.

BEPC Inc., founded in 2007, is a 100% employee‑owned company providing top-tier consulting and staffing solutions across industries like technology, engineering, manufacturing, and project management. At BEPC, we are driven by innovation and a commitment to excellence. We take pride in fostering a collaborative and innovative environment where our team members thrive. With competitive benefits, including medical, dental, vision, and life insurance, BEPC is dedicated to supporting our employees' personal and professional growth.