Research Scientist I, Attribute Sciences Computational Biology, AI & Scientific Informatics

Gilead Sciences • Santa Monica, CA

1d

About The Position

The Research Scientist I, Attribute Sciences Computational Biology, AI & Scientific Informatics will accelerate the adoption of artificial intelligence, agentic workflows, and advanced analytics across Analytical Development. The role combines biological sciences, bioinformatics, data science, and generative AI to build AI-powered tools that improve scientific productivity, knowledge management, data accessibility, and decision-making for process development and product knowledge involving viral vector-based gene delivery platforms and T cell therapies.

The scientist will partner with Process Development, Analytical Development, Manufacturing Sciences, Digital/IT, and Data Science teams to develop AI agents, retrieval-augmented generation (RAG) systems, workflow automations, and predictive models that use laboratory, process, and knowledge-management data. The role calls for strong communication with technical and non-technical stakeholders, curiosity about emerging AI capabilities, the ability to translate scientific workflows and needs into working products, and programming skills to independently build and deploy AI and data science solutions.

Requirements

• One of the following education and experience combinations: Ph.D. in Bioinformatics, Computational Biology, Data Science, Computer Science, or a related discipline; master's degree and 4+ years of experience; bachelor's degree and 6+ years of experience; associate degree and 8+ years of experience; or high school degree and 10+ years of experience.

Nice To Haves

• 3+ years of experience in AI, including experience with LLMs, vector databases, agentic frameworks, prompt engineering, and evaluation frameworks.
• Knowledge of advanced statistical techniques and concepts, and proficiency in statistical programming languages such as R, Python, or SQL to analyze data and draw insights from large datasets.
• Knowledge of cell biology, cancer biology, and/or immunology.
• Experience performing bioinformatics, including NGS analysis, and/or data analytics with high-dimensional data to drive business solutions.
• Experience with machine learning, statistical modeling, experimental design, and data visualization.
• Ability to think critically and demonstrate troubleshooting and problem-solving skills.
• Highly collaborative, with excellent interpersonal, verbal, and written communication skills.
• Self-motivated, detail-oriented, and willing to accept temporary responsibilities outside the initial job description.
• Comfortable in a dynamic, fast-paced environment.

Responsibilities

• Design and deploy Copilot, Copilot Studio, or similar AI agents to support scientific workflows.
• Develop RAG-based knowledge assistants that integrate information from enterprise knowledge sources.
• Create agents to answer scientific questions, retrieve and summarize technical information, generate draft reports, support investigations, assist with study planning and scheduling, and support operational excellence.
• Evaluate AI tool accuracy, groundedness, hallucination rates, performance, and citation quality.
• Analyze multimodal biological datasets, including NGS, omics, vector characterization, and cell therapy process data.
• Develop pipelines for automated data processing and visualization.
• Support digital transformation initiatives involving electronic lab notebooks and data lake infrastructure.
• Automate repetitive scientific workflows and documentation tasks.
• Build solutions that improve data discoverability and scientific knowledge reuse.
• Work with scientists and IT and digital teams to identify opportunities for AI to improve productivity.
• Translate scientific business problems into technical AI solutions.
• Train stakeholders on effective use of AI tools and prompt engineering techniques.
• Build predictive and descriptive models to support process development and manufacturing.
• Develop statistical tools to identify relationships between process parameters and manufacturing outcomes.
• Design dashboards and decision-support systems.

Benefits

• May be eligible for a discretionary annual bonus.
• May be eligible for discretionary stock-based long-term incentives; eligibility may vary by role.
• Paid time off.
• Company-sponsored medical insurance.
• Company-sponsored dental insurance.
• Company-sponsored vision insurance.
• Company-sponsored life insurance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree