Data Scientist Stagiaire (F/H)

At Konecranes, we believe that great customer experience is built on the people behind the Konecranes name. Everything we do, we do with passion and drive. We believe diversity drives business success and is the foundation for our growth. We welcome different backgrounds and skills that enrich our community and we promote a place where we can ALL be ourselves. This is what makes Konecranes a unique place to work.

The Data Science Lab team is looking for an enthusiastic and curious Data Scientist Trainee to complete our current roster. We are seeking a team player with strong motivation to contribute to our different projects.

Our Trainee main mission is to contribute in some initiatives inside our Lab. Our Trainee will be involved to develop different data science use cases to help the different business areas and business units in Konecranes. This mission will allow our Trainee a diversity of themes and interlocutors since he will interact with a lot of different profiles (business stakeholders, domain experts, data engineers, machine learning engineers, etc).

Two main areas in which our Trainee will probably be involved in: predictive Maintenance (identify sales opportunities from our connected assets) and GenAI field (reinforcing our dedicated team and exploring new trend in this field). This will be mentored by one of our Data scientist who will accompany our Trainee during his whole internship with us.

The candidate must have excellent relational skills with a great capability to solve complex problems; should enjoy the collaborative work and would like to grow as a professional inside our team.

Main missions:

· Interacting with multidisciplinary people inside the organization (business stakeholders, data profiles, IT)

· Analysing internal data from Konecranes

· Developing predictive models by using machine learning algorithms in order to solve concrete business problems

· Exploiting structured and unstructured data to turn them into insights

· Participating actively to the Agile development of the team

· Communicating advancement of projects and issues encountered to the AI Product Owner

· Being proactive inside the Data Science Lab

· Techno watch in Data Science and IA and experimenting new approaches

Master’s degree (last year) in computer science, AI, Data Science or Machine Learning engineering related fields. Strong understanding of machine learning notions such as neural networks, NLP, classification, regression, clustering, random forests, etc. Good understanding of generative AI concepts such as Large Language Models (LLM), Retrieval-Augmented Generation (RAG), embeddings... Proficient in Python and Machine Learning. Fluent in English.

Curious about data science and AI, with a keen interest in generative AI advancements.

Comfortable with working using the agile methodology (Scrum). Eager to learn, Team player, good communication, open to continuous improvement, proactive, curious

If you think you match to this description, please contact us!

At Konecranes, we believe that great customer experience is built on the people behind the Konecranes name – people committed to providing our customers with lifting equipment and services that move what matters. Everything we do, we do with passion and drive.

We believe diversity drives business success and is the foundation for our growth. We welcome different backgrounds and skills that enrich our community, and we promote a place where we can ALL be ourselves. This is what makes Konecranes a unique place to work.

Konecranes moves what matters. We are a global leader in material handling solutions, serving a broad range of customers across multiple industries. We consistently set the industry benchmark, from everyday improvements to the breakthroughs at moments that matter most, because we know we can always find a safer, more productive and sustainable way. That's why, with 16 000+ professionals in over 50 countries, we are trusted every day to lift, handle and move what the world needs.

Konecranes is committed to ensuring that all employees and job applicants are treated fairly in an environment which is free from any form of discrimination.