We are now looking for a Data Scientist / Data Engineer with an edge in graph technologies to join our Applied AI team here at Stiftelsen Chalmers Industriteknik!

About the role
As a Data Scientist / Data Engineer, you will work on a range of projects as part of our Applied AI team. As a Knowledge Graph Engineer, you will help us build and maintain scalable, intelligent data solutions in the health space. You will be involved in the hands-on development of both internal and external projects, applying data science techniques and machine learning to help solve real-world challenges.

Key Responsibilities

• Design, develop, and maintain knowledge graphs, ontologies, and semantic models.
• Integrate structured and unstructured data sources to enhance interoperability and data linking.
• Implement graph-based machine learning and reasoning techniques.
• Work closely with data scientists, software engineers, and domain experts to build AI-driven solutions.
• Optimize query performance for large-scale graph databases.
• Ensure data quality, consistency, and adherence to semantic web standards.
• Stay up to date with emerging trends in knowledge representation, linked data, and AI.
• Participate in other data science and applied AI projects, both internal and external
• Develop and implement data models / machine learning techniques, and data-driven solutions

About You
We are looking for someone with a solid background in data science and graph technologies. You are skilled in problem-solving, service-oriented, and capable of working in a structured and independent manner. You also communicate effectively with both technical and non-technical individuals. Flexibility and the ability to manage multiple tasks simultaneously will help you succeed in this role.

Qualifications

• Master’s degree in data science, or related field.
• Strong experience with RDF, OWL, SPARQL, and other semantic web technologies.
• Hands-on expertise with graph databases such as Neo4j, GraphDB, or Amazon Neptune.
• Proficiency in Python, Java, or another programming language commonly used for data engineering.
• Knowledge of ontology engineering, and data modeling.
• Experience integrating knowledge graphs with AI/ML pipelines.
• Strong problem-solving skills and ability to work in interdisciplinary teams.
• Prior work experience in the health care sector and practical knowledge about LLMs are highly advantageous.
• Good language skills in English, both spoken and written.

Employment Details and Application Process

This is a permanent, full-time position (standard office hours) based at our office in central Gothenburg, near the Chalmers campus. A six-month probation period applies.

Application deadline: March 28th.

We will review applications and conduct interviews on an ongoing basis. Emphasis will be placed on personal suitability during the selection process.

What We Offer
At Stiftelsen Chalmers Industriteknik, we offer a dynamic and innovative environment within an expanding organization focused on problem-solving and creating a sustainable future. Here, you’ll have the chance to leverage your skills while also finding opportunities for personal and professional growth. Join our growing organisation and you’ll enjoy benefits such as flexible working hours, a generous holiday allowance (30 days), a company pension scheme, a great wellbeing passport, lunch time training, monthly massage at the office - the list goes on!

Contact
If you have any questions about the position or Stiftelsen Chalmers Industriteknik, please feel free to reach out to:

Bernd Ketzler, group manager Applied AI – bernd.ketzler@chalmersindustriteknik.se
Susanna Turja, HR partner – susanna.turja@chalmersindustriteknik.se

We look forward to your application!

About us
Stiftelsen Chalmers Industriteknik is a research and development organization dedicated to driving innovation for a sustainable society. We are a passionate team of innovators, researchers, and project managers driven by the desire to make a difference for the future. By enhancing Sweden's capacity for innovation and making research accessible, we work to shape a better and more sustainable world. We are preparing tomorrow for the future.