Principal Data Scientist - RDT Applied AI

Roche•South San Francisco, CA

4d•$185,200 - $343,900

About The Position

Are you ready to use state-of-the-art AI to accelerate the journey of life-saving therapies from development to the patients who need them most? Imagine acting as the bridge between cutting-edge machine learning and critical business strategy. We are looking for a visionary Principal Data Scientist to serve as a premier technical consultant to our business, providing critical advisory support to high-priority use cases across our Pharma Commercial and Product Research & Development (R&D) team. Rather than owning the day-to-day delivery of a single project, you will operate in a highly dynamic, cross-departmental landscape—acting as a strategic consultant across a broad portfolio of initiatives to guide multiple teams in transforming complex data into the predictive and generative engines that power our next generation of healthcare innovations. The Principal Data Scientist - RDT Applied AI is a high-impact consulting role where advanced technical expertise meets business strategy in a highly regulated environment. Acting as an embedded consultant and strategic partner to our Pharma Commercial and Product R&D teams, you will guide the design and architecture of complex data science and AI solutions. You will evaluate commercial challenges, product development pipelines, and market dynamics to advise on sophisticated AI frameworks that drive measurable business value. Crucially, you will act as a champion for Roche’s existing AI and data platforms. You will promote their re-use across the enterprise while simultaneously gathering insights from top-priority use cases to influence the strategic roadmap of these platforms, identifying tech gaps and new requirements. This role requires deep expertise in advanced machine learning, generative AI, experimental design, and healthcare compliance. You will balance technical advisory with strategic leadership—shaping technical roadmaps, optimizing deployment strategies, and mentoring talent, all while advising senior business leaders on the art of the possible with AI in a regulated pharma environment.

Requirements

Master’s degree in Biostatistics, Computer Science, Data Science, or a relevant discipline required. PhD is strongly preferred.
A minimum of 7 years of direct, related experience in Data Science working intimately with AI/ML technologies.
Consultative Track Record: Proven experience working closely with senior leadership to inform, influence, and consult on high-level strategic business decisions. Experience advising rather than strictly executing is highly desired.
Industry & Compliance Knowledge: Demonstrated familiarity with the pharma/healthcare environment. A strong understanding of the compliance, regulatory (GxP), and data privacy implications of deploying AI in a healthcare setting is required.
Platform & Strategy Influence: Demonstrated experience in designing, promoting, and implementing enterprise-wide data science frameworks, platforms, and organizational best practices.
Execution Advisory: Extensive experience guiding complex data science projects from end-to-end and driving significant, quantifiable business impact through advisory and architectural design.
Programming & Analysis: Deep expertise and expert-level proficiency in multiple programming languages (Python is essential; R is a plus) and sophisticated data analysis.
AI/ML Expertise: In-depth understanding and hands-on capability with state-of-the-art machine learning, GenAI techniques, and experimental design.
System Integration & Platform Architecture: System integration experience is essential. You must deeply understand the generative process of AI and how to architect systems that dynamically pull information from diverse, disparate business sources, with a focus on leveraging centralized enterprise platforms.
Data Architecture: Strong background in data architecture, with the ability to advise on managing enterprise-level datasets, optimizing model performance, and ensuring successful deployment and continuous monitoring in production.

Nice To Haves

Consultative Mindset: Exceptional ability to listen to business stakeholders, identify root problems, propose data-driven solutions, and advocate for platform adoption in a collaborative, advisory capacity.
Leadership: Strong leadership and mentorship capabilities, with a proven ability to oversee the strategy of multiple projects simultaneously and guide data scientists executing the work.
Vision: A strategic mindset with the ability to shape the broader data science vision of the organization and influence enterprise platform roadmaps.
Communication: Excellent stakeholder management and presentation skills, capable of bridging the gap between deep tech, regulatory compliance, and overarching business strategy.

Responsibilities

Strategic Internal Consulting: Act as a dedicated advisor to Pharma Commercial and Product R&D teams on their highest-priority AI initiatives. Translate ambiguous business and product challenges into robust AI/ML strategies, consulting with the project owners to ensure technical solutions directly advance commercial goals and development timelines.
Platform Advocacy & Roadmap Influence: Actively promote and propose the use of Roche's current AI platform capabilities to project teams to maximize re-use and efficiency. Simultaneously, use your vantage point across key projects to identify technological gaps and feed new requirements back to the platform engineering teams, directly influencing the overarching AI platform roadmap.
Healthcare Context & Compliance: Apply a deep understanding of the pharmaceutical and healthcare environment to all consultative work. Ensure all proposed AI architectures and machine learning solutions are designed with a thorough understanding of the compliance, data privacy, and regulatory implications (e.g., GxP) inherent in healthcare data.
Stakeholder Management: Partner closely with senior leadership across Commercial and R&D to inform high-level strategic decisions. Act as a trusted translator who can explain complex algorithmic generative processes and compliance requirements to non-technical business partners.
Advisory Leadership: Oversee the architectural and strategic direction of multiple end-to-end data science projects by guiding the data scientists executing the work. Innovate and advise on cutting-edge AI initiatives that push the boundaries of the organization's technical capabilities.
Impact & Strategy: Lead the consultative phase of high-impact projects that significantly influence overarching business strategy. Play a key role in shaping the AI vision, frameworks, and best practices across the organization.
Accountability & Problem Solving: Tackle highly complex problems by developing bespoke analytical strategies. Advise teams on ensuring the absolute robustness, scalability, and longevity of deployed models in production environments.
Business & Technical Ability: Leverage expert-level proficiency in multiple programming languages and sophisticated data analysis to consult on solving the business's most ambiguous challenges, even if data ownership sits with the execution teams.