Gilead's AI Research Center (ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing 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.
- 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.
- Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations.
- 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.
- Act as a force multiplier for our data science team.
- Coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning.
- Serve as a bridge between technical teams and business stakeholders.
- 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.
