Data Scientist - Innovation Team

Are you passionate about the potential of Small Language Models (SLMs) and their ability to revolutionize Master Data Management (MDM)? Do you envision a future where agentic workflows streamline critical use cases in MDM? Join our Innovation Team, where we push the boundaries of technology to solve real-world data challenges.

This is the role and main tasks
As a key player in our Innovation Team, you will leverage SLMs to empower and optimize master data processes. Your work will focus on developing and deploying advanced models that improve data quality, automate complex workflows, and recommend the next best action in data management tasks. By harnessing the power of agentic workflows, you’ll help transform how businesses handle their data within our multidomain MDM platform "STEP" and our cloud-based Data-as-a-Service offerings.

More specifically you will

• Explore the potential of SLMs to solve automation and data management challenges.

• Design and implement agentic workflows that autonomously manage and maintain master data processes.

• Train and fine-tune SLMs using live data from our enterprise customers.

• Collaborate with DevOps teams to deploy and integrate these models across our cloud environments.

This is your Team
You will be part of a global Innovation Team, working alongside talented professionals from Denmark, England, Germany, the United States, and beyond. Our agile team embraces rapid prototyping, co-innovation, and close collaboration with clients to bring new solutions to life. With daily interactions and a strong focus on teamwork, we foster a culture of creativity and mutual support.

Some of the technologies we play with includes:

• Python

• Small Language Models (SLMs) and related frameworks

• Agentic workflows

• Experience with machine learning libraries (scikit-learn, PyTorch) and microservices

• Docker, Kubernetes, and Azure cloud environments

Who we are looking for
You are someone with a relentless curiosity for experimenting with new ideas and technologies. You are curiously interested in the future of SLMs and agentic workflows, especially how they can address critical MDM use cases. You push boundaries, and you thrive in a fast-paced, innovation-driven environment.

Qualifications

• A master’s degree in data science, computer science or a related field, with a strong focus on machine learning and AI.

• 3 to 5 years of experience with AI / ML – or fresh out of university

• Experience with the Microsoft Azure AI stack

• Knowledge about microservices and cloud platforms (Azure, Docker).

• A passion for agentic workflows and their applications in real-world scenarios.

We offer
At Stibo Systems, we offer more than just a job. We put people first and inspire you to become the best version of yourself.

• A flexible hybrid work model that supports work-life balance.

• A multicultural, international team and career opportunities across the globe.

• A dynamic, caring, and inspiring work environment focused on growth and well-being.

• Access to online learning platforms like Udemy for continuous upskilling.

Join Stibo Systems, where we embrace 'All Kinds of Data Minds.'

Stibo Systems is a global company with a Nordic heritage. We help companies transform into digital leaders through market-leading multidomain master data management that delivers transparency. Through our solution, large brands (our customers) connect data across their products, customers, stores, employees, suppliers, digital assets and much, much more.

Our people are key to our success and at Stibo Systems, you'll find an environment that values data driven, creativity, curiosity, and analytical thinking. We're committed to making you feel trusted, invested in, and connected, fostering a workplace where every data mind thrives. Be part of our journey to digital leadership!

Interested?
We invite candidates for interviews on a continuous basis, so apply soon! If you have any questions about the position, feel free to contact Jesper Grode, Director, Product Innovation, at [email protected].

Location: Aarhus