Data Scientist

Are you passionate about turning complex data into intelligent, production-ready solutions while supporting the future of open-access science? We are looking for a Data Scientist to join our team and help design, develop, and deploy advanced machine learning solutions that power intelligent, data-driven products. This role focuses on NLP, recommender systems, and agentic LLM workflows, turning complex business challenges into scalable and impactful analytical solutions.

This is an opportunity to work at the forefront of machine learning and AI, contributing to innovative systems that leverage state-of-the-art research in practical applications.

Core Responsibilities

• Design, develop, and evaluate machine learning and statistical models, with a focus on NLP, recommender systems, and LLM-based solutions.
• Translate business problems into data-driven approaches and scalable analytical solutions.
• Perform data exploration, preprocessing, and feature engineering to ensure high-quality inputs for modeling.
• Develop, optimize, and benchmark models using appropriate metrics and validation strategies.
• Build and experiment with LLM-powered systems, including agentic workflows and RAG.
• Investigate, reproduce, and compare research prototypes and state-of-the-art methods.
• Collaborate with engineering teams to support the integration of models into production.
• Monitor and analyze model performance and iterate to improve accuracy and robustness.

Additional Responsibilities

• Supervising Master/ Ph.D. students when there are trainees in the team.
• Representing the company in e.g. attending conferences, writing scientific articles.

Requirements

• Bachelor’s degree/ Master's degree in Computer Science or related.
• 2-5 years of experience as a Data Scientist.
• 2–5 years of experience in Python (including complex applications), Machine Learning, and LLMs.
• Strong background in data science, statistics, and analytical problem-solving.
• Intermediate proficiency in FastAPI, Celery, and Keycloak.
• Intermediate proficiency in PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Proficiency in Natural Language Processing (NLP), including tokenization and named entity recognition (NER).
• In-depth understanding of Artificial Intelligence principles.
• Strong working knowledge of Microsoft O365 tools.
• Excellent written and spoken English.
• Excellent communication skills, capable of conveying complex technical concepts to non-technical stakeholders.
• Ability to work effectively both independently and as part of a team.

Nice to have

• PhD in Computer Science or related.
• Leadership skills with the ability to mentor and guide junior engineers and interns.

About MDPI

Headquartered in Switzerland, MDPI is a fully Open Access publisher with a portfolio of more than 500 journals across all scientific disciplines. To date, MDPI has published the works of over 4.5 million researchers, collaborating with an extensive network of academic institutions and scientific societies worldwide. Above all, MDPI is committed to ensuring that high-quality research is freely accessible to readers across the globe.

At MDPI, technology is not just a support function - it’s a core driver of our innovation, performance and customer experience. We are proud to develop most of our software in-house and host our systems on-premises, further enriching our already diverse technology landscape. Our commitment to building on open-source stacks empowers our teams to work with flexible, modern and community-driven tools. From cutting-edge submission systems to advanced digital services, our IT environment is a dynamic playground where creativity meets complexity. With a strong focus on continuously growing our technology capabilities, MDPI offers a unique opportunity to work at the forefront of digital transformation in publishing. Join us and be part of a team where your ideas matter, your skills are valued and your passion for technology can truly thrive.

Initiatives

At MDPI, we develop and maintain various platforms in order to better serve the scientific community. Please find here-below a list of our main platforms:

https://www.mdpi.com/

https://sciprofiles.com/

https://sciforum.net/

https://www.scilit.net/

https://www.preprints.org/

https://encyclopedia.pub/

https://www.mdpi.com/books/

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