Data Scientist - Applied AI

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 Data Scientist - Applied AI At Roche Digital Technology (RDT), innovation meets purpose. As a global community of business-minded technologists, we are shaping the future of digital healthcare. Our mission is to power Roche through cutting-edge technologies—harnessing artificial intelligence, data, and scalable tech innovations. Driven by passion, we build digital solutions that enable smarter ways of working, unlock human potential, and drive meaningful breakthroughs for patients worldwide. Work Environment & Schedule We balance flexibility with in-person connection, averaging two days per week in the office for workshops, town halls, team meetings, and collaborative events. Because we operate across global time zones, this role requires frequent availability during late afternoons and evenings (after 5:00 PM–6:00 PM). About Our Team: Partnering Digital Solutions Join our Partnering Digital Solutions team, a strategic group focused on maximizing partnership impact through digital and AI-enabled ecosystems to advance the Pharma and DIA Partnering business. We are at the forefront of innovation - building scalable data infrastructure, applying advanced data engineering practices, and integrating cutting-edge external capabilities to accelerate decision-making and unlock business value. Our work spans across multiple high-impact initiatives, from developing intelligent data products to enabling end-to-end AI workflows. Whether it’s structuring complex data ecosystems or collaborating with external research institutions, this is a unique opportunity to help shape the future of data and AI at Roche by directly supporting key strategic decisions across our global Partnering organization. Responsibilities As a Data Scientist, you will play a critical role in shaping and delivering AI and machine learning capabilities across the Partnering Digital Solutions ecosystem. You will work closely with product owners, data engineers, architects, and business stakeholders to develop scalable machine learning models, intelligent workflows, and data-driven solutions that improve visibility, prioritization, operational efficiency, and strategic decision making. This role focuses on applied AI, machine learning, predictive modeling, and operational intelligence rather than purely research-oriented AI. You will help translate complex business challenges into scalable AI and analytics solutions that create measurable business impact across partnering operations. You will be responsible for: Machine Learning & Applied AI Solutions Design, develop, and deploy machine learning and AI-enabled solutions that support partnering activities such as opportunity prioritization, portfolio intelligence, forecasting, operational insights, and decision support. Apply advanced analytics, statistical modeling, machine learning, and emerging AI techniques to solve complex business problems and deliver scalable intelligence capabilities across the partnering ecosystem. Model Development & Experimentation Lead exploratory data analysis, feature engineering, model selection, training, validation, and performance evaluation for machine learning and AI-enabled solutions. Design and evaluate multiple modeling approaches, establish appropriate evaluation metrics, and optimize models for scalability, reliability, and business impact. Business Problem Solving & Decision Support Partner closely with business stakeholders and product teams to translate complex business challenges into analytical approaches, machine learning solutions, and scalable intelligence capabilities. Support data-driven prioritization and strategic decision making through actionable insights, predictive models, and operational intelligence. AI & Intelligence Enablement Collaborate with AI, data, and engineering teams to operationalize AI-enabled capabilities and support the adoption of scalable intelligence solutions across partnering platforms and workflows. Evaluate and apply modern AI techniques including predictive modeling, NLP, LLM-enabled workflows, and intelligent automation approaches to enhance partnering operations and decision making. Data & Intelligence Development Design and develop analytics solutions, dashboards, KPIs, and intelligence capabilities that improve visibility into partnering operations, opportunities, and portfolio activities. Support development of operational intelligence capabilities that enable proactive and informed business decisions. AI Operationalization & MLOps Collaborate with engineering and architecture teams to support operationalization of machine learning and AI-enabled solutions in production environments. Support scalable deployment, monitoring, observability, and lifecycle management of AI and machine learning capabilities aligned with enterprise AI standards and governance practices. Data Storytelling & Communication Communicate analytical findings, model outputs, and AI-driven insights through clear visualizations, presentations, and storytelling that support business understanding and stakeholder decision making. Translate complex analytical and machine learning concepts into practical business insights for both technical and non-technical audiences. Collaboration & Continuous Improvement Work in a cross-functional Agile environment and collaborate closely with product owners, data engineers, architects, vendors, and business stakeholders to continuously improve AI capabilities, analytics solutions, and operational intelligence across PDS. Contribute to evolving AI practices, engineering standards, experimentation frameworks, and continuous improvement initiatives across the organization. Qualifications Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related quantitative field. 5+ years of experience in data science, applied AI, machine learning, or advanced analytics solution development. Strong experience designing, developing, evaluating, and deploying machine learning models for business applications. Strong proficiency in Python and machine learning/data science frameworks such as scikit-learn, TensorFlow, PyTor