Delivery Service Manager - RDT Biometrics and Clinical Evidence

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.

The Position Job description The Delivery Management Professional (SE6) leads moderately complex deliveries, proactively identifies improvements, manages diverse stakeholders, and contributes to strategic implementation. In this role, you will independently define and control the scope of medium to large initiatives, involving multiple multidisciplinary teams, utilizing effective facilitation and analytical skills to drive value delivery. While navigating intricate stakeholder environments, you will connect team development with broader business objectives. Depending on the organization's needs, you may operate within role archetypes such as Project Manager, Service (Delivery) Manager, ITSM Process SME, Scrum Master, Release Train Engineer (RTE), or Agile Coach. Description of the area This team plays a critical role in drug development, integrating clinical study data, real-world evidence, and enabling cross-ecosystem collaboration to drive operational excellence and scientific innovation. They also deliver real-time operational insights from clinical trials, enabling proactive management of study execution, improving enrollment strategies, and streamlining workflows for maximum efficiency. By fostering collaboration across registries and federated open science networks, they leverage shared data ethically to uncover new scientific insights and study long-term treatment outcomes. Additionally, the team harnesses RWE and secondary use of clinical trial data to understand real-world treatment effectiveness, utilization patterns, and patient health trends. This holistic approach ensures trials are efficient, evidence generation is robust, and therapies are aligned with real-world patient needs, accelerating development timelines and improving outcomes at every stage. A key focus of the area will also be building AI-ready data foundations that support advanced analytics, machine learning, and emerging agentic AI capabilities. This includes engineering trusted, well-governed, and semantically rich datasets; enabling metadata-driven access; and providing reusable data products that allow autonomous and human-in-the-loop AI systems to safely explore, reason over, and act on complex clinical and real-world data. Job Responsibilities