Job Description
Are you looking for a thesis topic where you can make a real impact? We are now looking for two Master’s thesis workers to join Valmet Flow Control Global Operations Development team in Vantaa, focusing on enhancing data-driven decision-making in our global manufacturing operations.
Both theses focus on utilizing real production, product, customer and quality data to better understand, predict and prevent delivery delays in complex industrial projects.
The thesis workers will have access to real-life industrial data and will work closely with operations and development experts. The topics are highly relevant for Valmet’s business, and the results are expected to be used in further development of our operational practices.
Below thesis topics exact title and content are to be agreed between Valmet - Thesis student - Faculty staff thesis supervisor.
Thesis 1 - Predictive Analytics for Delivery Delays
The objective of this thesis is to develop a prediction model that estimates the risk of delivery delay already when a new customer order is received. The work focuses on identifying order, product and production parameters that have a strong correlation with delivery delays, and using these findings to build a reliable early warning model.
Typical research questions may include:
Which order or product characteristics are the strongest predictors of delivery delays?
How accurate can delay predictions be using historical production data?
Key to success in this thesis is strong interest and capability in working with large datasets, combined with programming and analytical skills.
Thesis 2 - Root Cause Analysis of Production Delays
The objective of this thesis is to identify and analyze the root causes behind the most common delivery delay reasons in Valmet Flow Control operations. The focus is on identifying key input parameters and process characteristics that drive delays and proposing a data-driven management and decision-support approach to mitigate them.
Typical research questions may include:
Which production, supply chain or organizational factors drive the most significant impact into delays?
How do different factors interact and accumulate into major delivery delays?
How can data be used to support proactive management and operational decision-making?
Key to success in this thesis is the ability to combine data analysis with studies of production management and lean principles.
Desired Background
Student in a relevant Master’s level program (e.g. Industrial Engineering, Data Science, Applied Mathematics, Operations Management)
Experience or interest in data analysis, statistics, machine learning or similar methods
Programming skills such as Python, R, SQL or similar
Interest in industrial processes and real-world operational problems
Practicalities
The thesis can be conducted either in English or Finnish
Due to a global working environment, good command of English is required; Finnish is a plus
Valmet will hire the thesis worker under a 6-month temporary employment contract with competitive salary
Starting time is flexible: earliest in June and latest by September 2026
Flexible working model combining remote and office work; office location in Vantaa, Finland
We Offer
An opportunity to work on an impactful, real-life industrial problem where your work contributes directly to improving delivery reliability towards customers. Valmet is one of the largest technology companies in Finland, offering strong opportunities for future career development both domestically and globally.
Additional Information
Did we catch your interest? For more information, please contact: Mikko Rovio, Director, Global Operations Footprint Development, [email protected].
If this opportunity sounds like a fit for you, apply soon, latest by June 14, 2026. We review applications during the application period, and the positions will be filled as soon as suitable candidates are found.
Valmet Finland is a smoke-free workplace.