Assoc Director, Data Scientist

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

Job Description

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.

You will be a thought leader 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.
• Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning.
• 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.
• Influence and Advise: 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.
• Stay Ahead: Continuously monitor the landscape of machine learning…