





Are you looking for an internship that provides hands-on experience in marketing data, analytics and technology within research publishing, and the chance to make connections at one of the largest publishers of education and research content? The Springer Nature Opening Doors internship in Marketing Data & Personalisation is a paid opportunity in Berlin, Germany, for students and recent graduates to gain experience in research, education and science publishing through data-driven marketing and customer engagement initiatives. Many perspectives and lived experiences remain underrepresented in the publishing industry. This underrepresentation has historically affected a wide range of groups, including Black people, Indigenous people, and people of colour, first-generation university students, people from socio-economically disadvantaged backgrounds, LGBTQ+ communities, people from underrepresented social castes, religious minorities and people with disabilities or neurodivergent conditions. We are looking for talented candidates from all backgrounds, with excellent skills in a range of fields, and we are committed to creating an inclusive internship, with a cohort that reflects a broad range of voices and experiences. The successful applicant will spend up to six months within Marketing Data, Analytics, and Technology, part of the Research Marketing division of Springer Nature. If selected for this internship, you will be embedded in a team working at the intersection of marketing, data and technology, gaining hands-on experience with real-world customer data, tools and processes that directly support global marketing initiatives. You will: Translate business needs for a more personalised customer experience into data-driven approaches Collaborate with data engineering and analytics teams to understand data sources, schemas, and customer data flows Support the building and maintenance of customer segments within marketing tools, ensuring accurate audience definitions for activation Analyse customer behaviour, engagement patterns and trends to inform segmentation and personalisation strategies Prepare, validate and optimise audience extracts using customer attributes and behavioural signals Contribute ideas to improve segmentation models, customer scoring logic and overall data-driven marketing effectiveness