Financial Data Engineering / Business Data Analytics Trainee — Patent Portfolio Management

Nokia’s Technology Standards business group licenses Nokia intellectual property, including one of the industry’s leading patent portfolios. Within it, Investment & Patent Portfolio Management Team turns complex patent portfolio and financial data into analysis that supports long-term investment decisions. The exact focus of the role depends on your strengths and interests. A more technical role centres on building reliable data foundations: bringing together data from different sources, resolving quality issues, inconsistencies, and missing values, and building and maintaining datasets, data pipelines, and practical tools that make patent cost and portfolio information easier to access and use. A more business-oriented role centres on turning that data into decisions: analysing patent portfolio and financial investment data, supporting investment modelling, cost-efficiency studies, scenario analysis, business cases, and demand and capacity planning, and presenting clear findings, their reliability, and the decisions they can support. Many tasks combine elements of both. This is a paid, full-time traineeships of 6–12 months in Espoo, with a flexible start date between January and summer 2027. To apply, please state which role you are applying for and submit the following documents in English: An anonymised CV (please exclude all personal information including name, email, picture in order for anonymised review); a short motivation letter including a 2 paragraph answer to the question: What would you do if you had all the patenting data in the world?; grade transcript / study transcripts, and your preferred start date and availability, including how long you can stay. Applications missing the requested documents will not be considered. Deadline: 30 November, 2026 We welcome applicants from any academic field. Your approach to problems matters more than a specific degree. We are looking for: Interest in data, business, and finance. A systematic, detail-oriented approach and the curiosity to keep investigating. Ability to work independently with complex data and draw business-relevant insights. Working English, written and spoken with good communication skills. Active student status at an EU university throughout the traineeship is required. Familiarity with financial data, statistical methods, programming, software development, or AI coding tools can be useful, but we are more interested in how you think and work.