Data Scientist Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

Job description

The Senior IT Data Scientist is responsible for leading, developing, and implementing data-driven solutions to complex business problems. This role involves independently identifying analytical opportunities, conducting in-depth data exploration and analysis, and building, testing, and deploying predictive models using various machine learning techniques. You will contribute to projects from inception to deployment, leveraging strong programming, statistical modeling, and data visualization skills, while clearly communicating findings to both technical and non-technical stakeholders.

Operating in a highly regulated GxP environment, you will build specialized AI agents that assist Analytical Data Scientists across the clinical data lifecycle. This requires deep expertise in advanced generative AI, multi-agent architectures (e.g., LangGraph), Graph-based Retrieval-Augmented Generation (GraphRAG), and LLMOps. You will balance hands-on technical work with leadership responsibilities, frequently contributing to the team's technical roadmap.

Description of the area

The Clinical Submission Data and Content Generation & Reuse function focuses on modernizing the creation and management of clinical data and regulatory submission assets (data and content). It develops and deploys platforms for structured content management, enabling the reuse of approved components across documents. This group also pioneers the use of agentic AI to assist in generating, reviewing, and assembling complex submission assets (data and content), aiming to improve quality and reduce authoring timelines.

Job Responsibilities

- Scope / (Content Leadership): Leads the development and deployment of models. Works independently on specific data science projects from start to finish.

- Accountability/Problem Solving: Identifies and solves intermediate to complex data problems. Validates models and ensures their accuracy with minimal supervision.Tackles complex clinical programming challenges by developing bespoke multi-agent workflows. Examples include building proactive coding debuggers that parse verbose logs, classify errors, and automatically propose code/configuration fixes.