# Senior Scientist, AI for Translational Sciences at AstraZeneca

AstraZeneca is hiring a Senior Scientist, AI for Translational Sciences in Barcelona, Spain. Level rates it Builds AI ●●●●; you can [apply on AstraZeneca](https://jobsbylevel.com/go/667d750a-f741-4f8f-af1d-3c42ee1cf137?utm_medium=ai-agent).

AI Level 4, AI centrality 95 out of 100. Spain - Barcelona.

## Details

- Company: [AstraZeneca](https://jobsbylevel.com/companies/astrazeneca)
- AI level: AI Level 4 (score 95 out of 100)
- Location: Spain - Barcelona
- Posted: November 5, 2026
- Apply: https://jobsbylevel.com/go/667d750a-f741-4f8f-af1d-3c42ee1cf137?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-scientist-ai-for-translational-sciences-at-astrazeneca-e404cc

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## Description

Role Based in Barcelona : 3 days onsite/2 days work from home. Are you a specialist in AI/ML for molecular data analysis and exploratory biomarker discovery? Are you leveraging machine learning models with molecular data in your daily work? Do you want to make a significant impact on Oncology & Biopharmaceuticals R&D by applying your knowledge in a company that transforms scientific ideas into life-changing medicines? If so, AstraZeneca could be your next career destination! Accountabilities: Join our growing AI for Translational Sciences team to support AstraZeneca strategic initiatives in machine learning and bioinformatics analysis of molecular data, including DNA sequencing, single-cell and bulk transcriptomics, proteomics, spatial, and digital pathology. As an ML/AI bioinformatician with expertise in NGS omics data, you'll design and apply innovative computational & AI analysis methods to advance our research portfolio. Working within a team and maintaining the highest quality standards, your strong quantitative skills will help build AI modelling solutions and agentic systems to interrogate diverse molecular datasets, empowering researchers to use AI systems for data-driven decision-making, translational science, and biomedical knowledge generation. Essential Skills/Experience: Master’s degree in Bioinformatics, Computational Biology, Machine Learning, or a related field with 4+ years of applied experience in ML/AI molecular data analysis; or Ph.D. in Bioinformatics, Computational Biology, Machine Learning, or a related field Expertise in AI/ML modelling approaches to molecular (omics, imaging) data Strong statistical and model-evaluation skills, including appropriate baseline selection, patient-level and cross-study validation, prevention of data leakage, handling of confounding and batch effects, and assessment of uncertainty and generalisability Hands-on experience implementing and adapting deep-learning models using frameworks such as PyTorch, transformers, h uggingface_hub Deep understanding of at least one type of molecular profiling data (e.g. RNA or DNA sequencing) and experience in analysing human Illumina NGS data Understanding of drug discovery biology: target identification, target validation, mechanism of action, or translational science Experience using AI tools/agentic frameworks like coding copilots and research assistants Proven programming skills (Python essential) and familiarity with software development best-practices (end-to-end tests, unit testing, version control with git) Experience working in Unix/Linux environments, familiarity with package management (e.g. Conda) Cloud computing (preferably AWS) or High-Performance Computing (HPC) ‘Builder’ mindset, strategic thinker, and experience leading projects Strong, professional communication skills and excellent attention to detail, capable of developing effective collaborative relationships with diverse teams of technical and non-technical analysts, engineers, scientists, strategists Experience working within a team environment Desirable Skills/Experience: Experience working with patient data from clinical trials and biomarker development Experience with biological foundation models such as BulkFormer, scGPT and DNABERT Understanding of modern deep learning architectures such as Transformers, CNN and GRU Experience with exploring explainability of deep learning models on multi-omics data Well networked within external bioinformatics, NGS, and AI/ML communities Experience working in pharma or biotech R&D At AstraZeneca, we are committed to creating the future of medicine by becoming a healthcare provider beyond medicines. We focus on being truly patient-centric by using technologies to better understand diseases, develop new medicines, and support patients comprehensively. Our digitally-enabled Research & Development cycle enhances clinical trials, data collection, digital therapeutics for rapid diagnostics, wearables, machine learning, visual

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