Senior Data Scientist in Image Analysis

About the role

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. 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.

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).

Requirements

• 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).

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