About the company:
Navinci is a Swedish biotech company developing innovative technologies to study protein interactions in their native spatial context, with a strong legacy in in situ proximity ligation assay technology and a broad portfolio of products for spatial proteomics.
About the role:
We are looking for a Senior Data Scientist in image analysis to join Navinci and build scalable, automated pipelines for spatial interactomics. You will take strong ownership in designing and advancing computational methods, with a focus on creating robust, reproducible workflows that incorporate rigorous quality control and leverage deep learning to address complex biological questions. The work will support both internal R&D and external collaborations.
You will be part of a highly skilled, and growing team, playing a key role in advancing pipeline development and computational innovation. The role requires both independent problem-solving and effective collaboration in a dynamic environment, helping position Navinci at the forefront of spatial biology and emerging AI technologies.
Key Responsibilities
Design, develop, and maintain scalable, automated analysis pipelines and reproducible workflows with robust quality control for spatial interactomics data.
Develop novel computational methods and apply deep learning to address complex biological questions and enable new analysis capabilities.
Build internal tools and contribute to best practices in pipeline design, reproducibility, and code quality.
Collaborate with multidisciplinary teams and external partners to translate biological problems into computational solutions.
Mentor and guide junior team members while contributing to a collaborative, adaptive, and high-performing team environment.
Work effectively in a dynamic environment with adaptability, independence, and strong collaboration, while staying current with advances in spatial omics and AI (e.g., agentic/LLM-based workflows).
Qualifications
Required:
PhD in Computational Biology, Bioinformatics, Computer Vision, or a related field (or equivalent industry experience).
Strong understanding of spatial omics data and associated analysis challenges.
Demonstrated ability to design and develop robust, reproducible computational methods and pipelines, including components such as image processing, clustering, spatial analysis, statistical analysis and data visualization.
Strong proficiency in Python, with experience developing production-quality code for data analysis and pipeline development.
Proven, hands-on experience in developing and applying deep learning models, using machine learning frameworks (e.g., PyTorch, Scikit-learn).
Ability to independently solve complex, open-ended problems.
Strong communication and collaboration skills in interdisciplinary environments.
Preferred:
Industry experience in image analysis methods and/or pipeline development is a strong plus.
Experience with agentic workflows, AI agents, or LLM-based systems.
Experience applying best practices in scientific programming and/or software engineering (e.g., testing, debugging, version control, CI/CD).
Experience with GPU programming and performance optimization.
Experience with high-throughput computing such as HPC or cloud computing.
Experience with tool development, UI/UX, or containerization (e.g., Docker).
What We Offer
Opportunity to shape scientific direction in a cutting-edge company.
Agile teams with fast decision-making and direct impact.
Dynamic environment with growth and leadership potential.
Close collaboration across R&D, product, and commercial teams.
Applications will be reviewed on a rolling basis.