Trainee, Investment 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.
We are looking for a Financial Data Engineering Trainee to build reliable data foundations for patent cost and portfolio analytics. This is a hands-on technical role in which you will bring together data from different sources and resolve quality issues, inconsistencies, missing values, and material assumptions. You will also develop practical internal tools, visual outputs, and user interfaces that make complex information easier to access, understand, and use; as well as build and maintain datasets, data pipelines, and models for patent cost and portfolio analytics.
This is a paid, full-time traineeship of 6–12 months in Espoo, with a flexible start date between January and summer 2027.
To apply, please submit the following documents in English: An anonymised CV (please exclude all personal information including name, email, picture in order for anonymized review); a short 2 paragraph answer to 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 not be considered.
We welcome applicants from any academic field. Your approach to problems matters more than a specific degree.
Interest in data, business, finance, and software development.
A systematic and detail-oriented approach.
Working English, written and spoken.
Active student status at an EU university throughout the traineeship is required.
How you approach the work matters as much as what you already know. You might be someone who:
Gets curious when data looks strange and follows the trail until it makes sense.
Builds work that others can rerun, understand, and improve.
Knows that reliable data needs both technical care and clear explanations.
Checks their own output before anyone else has to.
We do not prescribe a toolset. The right answer may be a spreadsheet, code, a model, a visual, or a carefully documented assumption. We can teach you our stack; what matters is choosing the right tool for the problem.
We offer a place where you get to work in a diverse and inclusive team working on real patent portfolio and investment questions. You will have an opportunity to build datasets, tools, analyses, and findings that support real decisions, and learn through support from experienced colleagues.

Skills
Intellectual Property

Work arrangement
Hybrid