ppOn average, it takes more than 10 years to develop a drug and costs more than $1.3 billion. Over 70% of drug RD costs are spent on clinical development, yet the success rate from phase I to approval is only around 10%. At Evinova, a new health tech business as part of the AstraZeneca Group, we are on a mission to increase clinical trial success rates by 20%, accelerate clinical development timelines by 36 months, and reduce study costs by 50% by leveraging state-of-the-art AI and Machine Learning. /ppIf you are a rigorous modeler with hands‑on experience designing and validating ML solutions, a strong grounding in statistics and modern machine learning, a talent for turning data into trustworthy decisions, and a voracious learner, then you could be a fantastic fit for our team. /ppTalent with ambition to grow into leadership roles will be a key differentiator for successful candidates. Glass ceiling smashers especially welcome. /ppWe are seeking a highly skilled and innovative Principal AIML Scientist whose primary mission is to work hand in hand with our Clinical Operations and Clinical Development teams: to understand their problems deeply and design AI and advanced analytics solutions that significantly reduce the complexity of clinical trials. You will frame these problems quantitatively, design and run experiments, and apply proven statistical and machine learning methods to turn complex clinical and product data into trustworthy decisions. You’ll own model evaluation and clinical validation – from endpoints and study analysis to real‑world evidence – and partner with engineering to bring validated approaches into production, always grounding your work in real clinical needs. /ppOver time, you will become the subject‑matter expert within the AI Data Science team on clinical trial design and the processes that surround it, staying closely connected to science, clinicians, and medical experts so that everything the team builds is grounded in clinical reality. This position offers the opportunity to set the methodological bar for the team, mentor others in experimental rigor, and – at the senior end of the role – develop novel approaches when established methods fall short. You’ll be at the forefront of applying machine learning and statistical science to revolutionize clinical development and drug discovery. /ph3WHAT THE ROLE INVOLVES /h3ulliPartner directly with Clinical Operations and Clinical Development teams to understand their problems and the complexity in their day‑to‑day work. /liliIdentify and design AI and advanced analytics solutions that significantly reduce the complexity of clinical trial processes. /liliBecome the subject‑matter expert within the AI Data Science team on clinical trial design and the processes associated with running trials. /liliStay closely connected to science, clinicians, and medical experts to keep solutions grounded in clinical reality. /liliFrame healthcare problems quantitatively and design, build, and validate the models and analyses that solve them.



/liliDesign and run experiments to determine which approaches work and quantify their impact. /liliApply proven statistical and machine learning methods with rigor – experimental design, hypothesis testing, causal inference, and uncertainty quantification. /liliOwn model evaluation and clinical validation, including endpoints, overread, and real‑world evidence. /liliTranslate analytical results into clear, trustworthy product and clinical decisions, and communicate them to technical, non‑technical, and clinical stakeholders. /liliPartner with engineering to bring validated models and approaches into production. /liliMentor team members in methodological rigor, experimental design, and sound interpretation of results. /liliCollaborate in a multidisciplinary environment to align AI initiatives with business and clinical objectives and drive digital transformation. /liliStay current with advances in machine learning and statistics; where established methods fall short, develop and validate novel approaches the team can adopt. /li /ulh3QUALIFICATIONS /h3h3SKILLS AND CAPABILITIES NEEDED /h3ulliDegree in Statistics, Computer Science, Mathematics, Physics, or a related quantitative field; an advanced degree is preferred. /lili5+ years in data science or applied ML roles focused on modeling, experimentation, and validation. /liliStrong Python programming with proficiency in data science libraries such as NumPy, pandas, scikit‑learn, SciPy, statsmodels, Optuna, and TensorFlow/PyTorch. /liliStrong foundation in statistics and experimental design, including hypothesis testing, causal inference, and uncertainty quantification. /liliRigorous model evaluation and validation methodology, including handling of bias, data leakage, and generalization. /liliExperience designing and analyzing experiments and A/B tests, including settings with confounding or limited data. /liliHands‑on experience with generative AI and large language models (LLMs) – calling and integrating LLM APIs, prompt engineering, retrieval‑augmented generation (RAG), and evaluating LLM outputs for practical applications. /liliComfortable collaborating with engineers to move validated models toward production. /liliAdvanced SQL skills for querying and shaping large, complex datasets. /liliExperience working with clinical, health, or other regulated real‑world data. /liliCreative problem‑solving abilities and outside‑the‑box thinking. /liliExcellent communication skills for technical, non‑technical, and clinical audiences. /liliProven ability to partner with non‑technical domain experts – especially clinical teams – translate their problems into analytical solutions,



and build lasting trust. /liliDemonstrated innovation mindset and ability to work independently. /li /ulh3Desirable Skills/Experience /h3ulliExperience with clinical endpoints, overread, or real‑world evidence studies. /liliBackground in biostatistics, epidemiology, or causal inference. /liliData visualisation expertise. /liliExperience developing novel methods or publishing in peer‑reviewed venues. /liliExperience with Bayesian methods or probabilistic modeling. /liliFamiliarity with MLOps practices and partnering on model deployment. /liliKnowledge of healthcare AI/ML regulatory requirements. /li /ulpKnowledge of drug development, clinical trial design, and clinical operations; prior experience working in the pharmaceutical industry is nice to have but not required. /ph3Why Evinova (AstraZeneca)? /h3pEvinova draws on AstraZeneca’s deep experience developing novel therapeutics, informed by insights from thousands of patients and clinical researchers. Together, we can accelerate the delivery of life‑changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment. We know that regulators, healthcare professionals, and care teams at clinical trial sites do not want a fragmented approach. They do not want a future where every pharmaceutical company provides its own, different digital solutions. They want solutions that work across the sector, simplify their workload, and benefit patients broadly. By bringing our solutions to the wider healthcare community, we can help build more unified approaches to how we all develop and deploy digital technologies, better serving our teams, physicians, and ultimately patients. Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI to serve the wider healthcare community and create new standards for the sector. Join us on our journey of building a new kind of health tech business to reset expectations of what a bio‑pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting‑edge methods, and bringing unexpected teams together. /ph3Where can I find out more? /h3pOur Social Media, Follow Evinova on LinkedIn /ppLearn more about Evinova /ph3Date Posted /h3p31-jul-2026 /ph3Closing Date /h3p06-ago-2026 /ppAstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry‑leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non‑discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements. /p /p #J-18808-Ljbffr

📌 Principal AI&ML Scientist – Evinova (Barcelona)
🏢 Evinova
📍 Barcelona