Gilead's AI Research Center (ARC) is looking to spearhead the development of AI/ML to transform clinical development processes, optimize clinical trials, enhance data-driven decision-making, and provide support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives.
Requirements
- Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale.
- Profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes.
- Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes.
- Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring.
- Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers.
- Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers.
- Experience with code management using Git.
Responsibilities
- Spearhead the strategic vision for leveraging AI/ML within clinical development.
- Guide the full lifecycle of machine learning models from initial concept to real-world application.
- Architect scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers.
- Translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production.
- Research and develop cutting-edge algorithms to solve critical challenges.
- Design and implement the technical and process building blocks needed to scale our AI/ML capabilities.
- Continuously monitor the landscape of machine learning and biopharmaceutical innovation.
Other
- Partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions.
- Serve as a bridge between technical teams and business stakeholders.
- Skill in scoping project requirements and developing timelines.
- Knowledge of product management principles.
- Strong technical documentation skills.
