Über
Gilead's AI Research Center(ARC) is looking for a Senior Data Scientist to spearhead the development of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide technical expertise 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.
You will be an innovator in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development—from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers.
Responsibilities
Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll 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.
Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands‑on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers.
Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll 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.
Drive Breakthroughs: Research and develop cutting‑edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context.
Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines.
Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state‑of‑the‑art techniques to maintain a competitive edge.
Basic Qualifications
Doctorate and 2+ years of relevant experience OR
Master’s and 6+ years of relevant experience OR
Bachelor’s and 8+ years of relevant experience
Preferred Qualifications
Education: PhD with 2+ years of experience in data science within biotech or technology or Master’s with 8+ years. A degree in Software Engineering, Biomedical Engineering, Chemical Engineering, Computational Sciences, Biostatistics, or a similar field is required. Technical Skills:
Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes.
Data & Computational Proficiency: Fluent in Python or R and SQL, with hands‑on experience in building and optimizing data pipelines for analytical and model development purposes.
Cloud‑Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring.
Translational Research: 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.
Project Skills:
Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers.
Skill in scoping project requirements and developing timelines. • Knowledge of product management principles.
Experience with code management using Git.
Strong technical documentation skills.
Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers!
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Sprachkenntnisse
- English
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