Marketing Data & Personalisation Intern, Doors Programme

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 under‑represented in the publishing industry. This under‑representation 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 under‑represented 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.

• 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

• Developing skills in SQL or Python for data querying and validation
• Gaining practical experience in marketing segmentation, personalisation strategies and customer lifecycle marketing
• Exposure to BI and visualisation tools such as Looker, Tableau or Power BI
• Understanding data privacy principles, including GDPR and consent management
• A paid internship based in Berlin (in line with local market conditions)
• Hands‑on experience at one of the largest academic publishing groups and the opportunity to learn from experienced marketing and data professionals
• Support from a buddy from one of Springer Nature’s employee networks
• Access to career development, training and events, including an overview of different business areas at Springer Nature and advice on the job application process
• The opportunity to work on projects related to inclusion and sustainability in the publishing industry

Marketing Data, Analytics, and Technology is part of Springer Nature’s Research Marketing division. The team works at the forefront of data‑driven marketing, enabling more personalised and effective engagement with researchers, authors and institutional partners worldwide. By combining marketing expertise with analytics and technology, the team supports strategic decision‑making and enhances customer experiences across Springer Nature’s global portfolio.

• Currently enrolled in an undergraduate or graduate programme (e.g. Data Science, Business Analytics, Marketing, Computer Science or related field), or a recent graduate
• Available to start in June 2026 for an internship of up to six months
• Strong interest in marketing data, analytics and research publishing
• Basic SQL or Python skills for querying and exploring customer data
• Analytical mindset with the ability to interpret data and translate insights…