Cristina works in cross-functional teams (UX/UI, data, tech, editorial) to develop data products for the end-users (e.g. recommender systems in the app) and the NZZ’s internal users (e.g. decision support systems for journalists) and bring business value by leveraging AI technology (e.g. NLP techniques, supervised ML, causal ML). As product owner, her work ranges from educating about the opportunities and limitations of AI, defining vision, OKRs and business metrics, translating those metrics into detailed requirements (ML models, technical metrics, API specifications, etc.), planning, and working closely with the data scientists/ML engineers and data engineers to develop, deploy and continuously improve them in production. As the technical lead of the Data Science & Machine Learning area within the central Data team, Cristina defines the strategy and technical roadmap for NZZ’s MLOps platform, mentor and coach all Data Scientists & ML Engineers around all operational topics (algorithms, code, architecture, requirements, stakeholders, etc.)