Internship in Innovation & Sustainability - For students in the field of Data Science, Business Analytics, Health Economics, or Digital Transformation — Roche

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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 Our Global Internship Programme in Innovation & Sustainability (#IP2TIS) offers a unique opportunity for passionate individuals to gain hands-on experience in the pharmaceutical industry while making a positive impact on the world. Are you ready to join a global network spanning 20+ countries, where bright minds collaborate to tackle real-world challenges in Innovation & Sustainability? Do you want to work on impactful projects, shape the future, and drive change from within? You will contribute to the development of an AI-powered framework that automates the creation of personalized business cases for private and public diagnostics labs in Spain. The project aims to reduce a highly manual consulting process from weeks to minutes by combining market intelligence, ROI modeling, and generative AI to produce strategic narratives and financial cases tailored to individual lab profiles. Within your first 6 months, you are expected to help deliver a segmentation taxonomy of the lab ecosystem, a structured data model linking lab profiles to value dimensions, an AI-assisted prototype, validation with real-world Spanish lab profiles, and a replication guide for broader EMEA use. Your work will support Roche’s Access to Innovation and Equitable Health Outcomes priorities by helping labs adopt precision diagnostics more effectively and by quantifying the health equity impact of earlier and more accurate diagnosis. This internship offers a unique opportunity to bridge AI, healthcare consulting, and sustainability while shaping the future of precision medicine in Spain. The Opportunity

• Map the Spanish private and public lab ecosystem and identify key high-volume laboratory profiles relevant for strategic engagement
• Shadow the Spanish Consulting team to understand current manual workflows, data bottlenecks, and improvement opportunities
• Define ROI dimensions tailored to the Spanish market, including clinical, financial, and operational value drivers
• Develop AI prompts and framework logic to transform structured data into high-quality strategic narratives and business cases
• Quantify health equity metrics and integrate them into the value proposition of the tool
• Build and test an AI-assisted prototype for business case generation using relevant low-code or technical tools
• Validate the prototype with 3–5 real-world Spanish lab profiles in collaboration with the local consulting team
• Create a technical playbook to support scaling the framework across other Roche EMEA markets Who You Are You are enrolled or have completed your Master’s or MBA studies at a university, preferably in the field of Data Science, Business Analytics, Health Economics, or Digital Transformation within the last 12 months and are interested in applying your knowledge in a modern working environment as part of an internship of at least 6 months. Furthermore you are
• Experienced or strongly interested in Generative AI and LLMs, including prompt engineering and the use of AI tools to generate professional narratives from structured data
• Knowledgeable in business and ROI modeling, with an understanding of financial and operational KPIs in healthcare or laboratory settings
• Proficient in data analytics and visualization tools such as PowerBI or Tableau; familiarity with Python, Streamlit, or Microsoft Power Apps is an advantage
• A structured thinker with an entrepreneurial mindset who is comfortable working in ambiguity and turning complex inputs into practical solutio