Digital Solution Lead - Clinical

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 As a Clinical and Real World Evidence Digital Solution Lead (Technology Consultant), you possess a strong understanding of complex business and scientific workflows, data science workflows, AI/ML/GenAI technologies, and modern data platform capabilities including AI-ready data product requirements. You will support the identification, evaluation, development, and scaling of innovative data and AI capabilities across the real-world and clinical data ecosystem.

This role bridges business needs, data science expertise, evidence generation workflows, and platform engineering to ensure that new capabilities progress from idea and proof of concept into scalable, governed, and sustainable digital solutions. Acting as a trusted technical and data science partner, you will contribute to PoCs, product evaluations, data product roadmaps, productisation of innovative solutions. You will help ensure that emerging capabilities are evaluated for business value, scientific relevance, technical feasibility, scalability, governance, cost-effectiveness, and fit with the broader RW&C data ecosystem.

The Real World & Clinical Data Innovation area focuses on accelerating the use of real-world data and clinical trial data, to support evidence generation, clinical development, study simulation, and AI-enabled decision-making. The area works at the intersection of data science, platform engineering, data products, GenAI, governance, and business strategy. Its mission is to identify and scale capabilities that improve access to high-quality data, enable reusable data products, support advanced analytics, and accelerate the generation of reliable evidence.

• clinical insight layer development
• reusable data product delivery
• evaluation of external RWD analysis platforms
• novel data licensing models
• GenAI-enabled workflows
• study simulation enablement
• AI-ready data foundations

The Opportunity:

Accountability/Problem Solving:
Frames complex business problems, drives root-cause analysis, manages scope, and ensures engineering deliverables align with organizational objectives, including AI-ready data and ethical AI requirements. Stakeholder Management:
Engages stakeholders across organizational boundaries, acts as a trusted advisor to leadership, and drives alignment across teams. Impact/Strategy:
Delivers high-value solutions aligned with business strategy, evaluates strategic options and risks, and helps shape long-term roadmaps. Complexity / (Product Size):
Operates at product or product-line level, navigating evolving requirements and translating complex problems into scalable, production-ready solutions. Technical ability and hands-on expertise:
Applies strong technical, data science, and AI/ML/GenAI expertise to define AI-ready data products, evaluate solutions, and build PoC prototypes, with particular focus on GenAI and agentic AI, including their application in sensitive and regulated data environments. Data innovation and capability development:
Identifies and shapes data and AI capabilities for RWD, clinical data reuse, study simulation, and evidence generation. Translates scientific and business needs into scalable, reusable, and governed platform capabilities from PoC through productisation.

• University degree or equivalent experience in Data Science, Computer Science, Bioinformatics, Statistics, Engineering, Mathematics, Life Sciences, or another relevant scientific or technical field.
• Strong hands-on experience in one or more of the following: data science, machine learning, advanced analytics, applied AI, or GenAI, with the ability to independently evaluate solutions, build or contribute to PoC prototypes, and help progress capabilities toward scalable, production-ready solutions.
• Demonstrated experience leading complex, cross-functional data, AI, or digital initiatives, navigating ambiguity and aligning business, product, data science, and engineering stakeholders.
• Practical understanding of GenAI application patterns, such as assistants, retrieval-augmented generation, agentic workflows, natural-language interfaces, semantic search, or AI-enabled data discovery.
• Understanding of modern data platforms and data products, including data pipelines, metadata, semantic layers, ontologies, data quality, and cloud-based analytics environments.
• Ability to evaluate data and AI solutions holistically and translate complex business and scientific needs into clear solution requirements, considering business value, technical feasibility, model performance,…