Staff Scientist in AI and Data Engineering

The position is organisationally based in the Department of Computing Science, while the work is carried out within the framework of the Arctic Centre.
About the Department of Computing Science & the Arctic Centre
The Department of Computing Science at Umeå University is an international environment for research and education across a broad range of computing science. The department is internationally renowned for excellent research and teaching.
The Arctic Centre at Umeå University is a meeting place for transdisciplinary research and education, focusing on sustainability, climate, health, a just transition, green industrialisation, Indigenous perspectives and rural issues.
The Staff Scientist role will support the Arctic Centre’s activities by developing solutions for collecting, structuring, analysing and visualising complex research data.
Duties
This is a senior, research-oriented role for someone who wants to work with large and complex datasets, develop advanced analytical solutions and build the next generation of AI- and data-driven systems. You will work independently throughout the process, from defining the problem to delivering a complete, scalable solution.
Analyse and process large and complex research datasets, and quality-assure and structure data from relevant sources.
Design, develop and optimise advanced data pipelines and automated workflows for data collection, transformation, analysis and reporting, including integration with external data sources and APIs, identifying bottlenecks, and tuning for performance, scalability and stability.
Develop and maintain databases that handle multiple datasets and enable recurring, reproducible analyses.
Develop models and intelligent systems in AI and Machine Learning, including Deep Learning, transformer-based models, AI agents and AI techniques, that can combine and search information across large datasets.
Prepare requirements specifications and technical descriptions in dialogue with researchers and other colleagues, and develop dashboards and interactive visualisations that enable graphs and analysis results to be reproduced and adapted for publication on the web.
Contribute to technical architecture and methods development, and prepare and maintain documentation of code, databases, workflows and methodological choices for long-term use and further development.

You will work closely with researchers and other colleagues and contribute to shared procedures, templates and ways of working. The work is carried out iteratively and independently, in close dialogue with the organisation. Duties may vary over time.
Requirements
The position requires a PhD in Computational Science, Data Science, Computer Science or another field deemed equivalent by the employer, as well as several years’ experience in advanced data science work in a research or development environment.
The position also requires:
Strong programming skills, particularly in Python and SQL, and familiarity with databases and large-scale data management.
Extensive experience in developing, optimising and tuning data pipelines (ETL/ELT, data ingestion, transformation, automation and monitoring), as well as working with APIs.
Experience in AI and Machine Learning, including modern generative AI techniques, and the ability to assess when AI is the right solution and when traditional methods are more suitable.
Documented experience from a university, academic or research-related setting, and familiarity with working alongside researchers and specialists.
The ability to work in a structured and independent manner, develop and work from requirements specifications, and document technical solutions clearly and usefully.

Very good English language skills are essential, as the work takes place in a research-oriented and international environment.
We are looking for someone who is analytical, thorough and solutions-oriented, with good teamwork skills and a strong interest in research data, methods development and technical solutions. You enjoy solving problems where standard solutions are not sufficient, can communicate complex technical issues clearly, and can switch between strategic thinking and practical implementation.
Desirable qualifications
Experience in bibliometrics, research evaluation or working with research and publication data, as well as tools such as Web of Science, Scopus, Dimensions or similar.
Experience with reproducible analytical processes, data quality and structured data management in a research environment.
Experience in visualisation and dashboards, including reusable analysis and visualisation structures, as well as knowledge of JavaScript/TypeScript and React or other modern frameworks.
Experience with relational, document and graph databases (e.g. PostgreSQL, MySQL, MongoDB, Neo4j) and knowledge graphs, as well as additional languages such as R, C# or Python.
Experience building graph databases and dashboards for complex datasets is particularly valuable.
An interest in UX/UI and Human-Computer Interaction, as well as experience with agile or iterative ways of working in interdisciplinary projects that bring technology, data and research together.
Good Swedish language skills.

This is an opportunity to work on complex data and AI challenges in an Arctic, transdisciplinary environment and influence the development of the centre’s future analysis and data platforms. We are looking for someone who sees the whole process: from the research question and data collection, through large-scale data management, pipeline development and modelling, to visualisation and a scalable end solution. It is the combination of a PhD, data science, academic experience, AI and data engineering that makes the role unique, and means we are looking for a specialist rather than a traditional software developer or data analyst.
Other
The position is full-time and fixed-term for 12 months, starting 2026-12-07 or by agreement. A high level of presence in the organisation is required.
The application must include
Cover letter explaining why you are applying
CV/resumé
Documentation of formal qualifications (transcripts, degree certificates, course certificates, etc.)

Applicants may attach other documents relevant to the position. Applications must be written in Swedish or English.