AI Science & Engineering Analyst

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development, andcommercialisation of prescription medicines in Oncology, Rare Diseases, andBioPharmaceuticals, including Cardiovascular, Renal & Metabolism, and Respiratory & Immunology. We are committed to pushing the boundaries of science to deliver life-changing medicines, and we believe thatdata science and artificial intelligence are central to how we will redefine drug discovery and patient care over the next decade. 

About the Role 

We are looking for an exceptionalScientist or Senior Scientist to join our growingAI/ML for Translational and Clinical Sciences team, working at the intersection ofdigital twins, foundation models, and multimodal clinical data. In this role, you will design and build next-generation machine learning systems that predict clinical outcomes, discover novel biomarkers, and enable precision patient stratification across AstraZeneca's therapeutic areas. 

You will help buildpatient-level digital twins that integrate longitudinal clinical, imaging, genomic, proteomic, and real-world data—leveragingfoundation models to reason across modalities and time. Your work will directly inform trial design, endpoint selection, and translational decision-making,ultimately accelerating the delivery of transformative therapies to patients. 

This is a highly collaborative role sitting at the interface ofData Science, Clinical Development, Translational Medicine, and Biometrics, with strong exposure to therapeuticarea leadership. 

What You'll Do 

• Digital Twin Development: Design, train, andvalidate patient-level digital twin models that simulate disease trajectories and treatment response using longitudinal multimodal clinical data. 

• Foundation Model Research: Contribute to the development, fine-tuning, and evaluation of foundation models (transformer-based, generative, and multimodal) tailored to clinical and biomedical data, including EHR, medical imaging, omics, and free-text clinical notes. 

• Clinical Outcome Prediction: Build predictive and causal ML models for clinical endpoints, adverse events, disease progression, and treatment response, ensuring rigorous validation against prospective and external datasets. 

• Multimodal Data Integration: Develop scalable pipelines and representation-learning approaches that unify structured clinical, genomic, transcriptomic, proteomic, imaging, and real-world evidence data. 

• Biomarker Discovery: Apply interpretable ML and causal inference methods toidentify andvalidate novel prognostic and predictive biomarkers from clinical trial and real-world datasets. 

• Patient Stratification: Design ML-driven stratification strategies to support precision medicine hypotheses, enrichment trial designs, and companion diagnostic development. 

• Cross-Functional Collaboration: Partner closely with clinicians, statisticians, translational scientists, bioinformaticians, andMLOps engineers to translate models into decision-grade tools embedded in R&D workflows. 

• Scientific Leadership: Publish in top-tier venues (Nature Medicine,NeurIPS,ICML,Cell Patterns,Lancet Digital Health), represent AstraZeneca at external conferences, and contribute to strategic partnerships with academic and technology collaborators. 

• Regulatory & EthicalRigour: Ensure that models are developed in line withGxP,model risk management, fairness, privacy, and emerging regulatory guidance (FDA, EMA, MHRA) for AI/ML in drug development. 

At theSenior Scientist level, you will additionally be expected to shape scientific strategy, mentor junior scientists, lead cross-functional workstreams, and act as a technical authority in digital twin and foundation modelmethodology across the portfolio. 

Essential Requirements 

• PhD in Computer Science, Machine Learning, Computational Biology, Biomedical Engineering, Biostatistics, Physics, or a closely related quantitative disciplineOR anMS in a comparable discipline with equivalent applied research experience in AI/ML for healthcare or life sciences. 

• Demonstrable experience developingmachine learning or deep learning models applied to clinical, biomedical, or omics data. 

• Strongproficiency inPython and modern ML frameworks (PyTorch,JAX, orTensorFlow), including experience with distributed training on GPU/TPU infrastructure. 

• Solid understanding oftransformer architectures,self-supervised learning, andfoundation model training or fine-tuning paradigms. 

• Experience working withlongitudinal clinical data (EHR, clinical trials, registries) and familiarity with data standards such asOMOP,CDISC (SDTM/ADaM),FHIR, orDICOM. 

• Strong grounding instatistical inference,causal modelling, orsurvival analysis, and a rigorous approach to validation andgeneralisation. 

• Track record of scientific output throughpeer-reviewed publications, preprints, or open-source contributions. 

• Excellent written and verbal communication skills, with the ability to explain complex methods to non-technical stakeholders. 

Experience expectations by level: 

• Scientist: PhD with 0–3 years of relevant post-PhD experience,or MS with4+ years of relevant industry/research experience in applied ML for biomedical data. 

• Senior Scientist: PhD with5+ years of relevant post-PhD experience,or MS with8+ years of relevant experience, and a demonstrated record of leading end-to-end ML projects and influencing scientific or product strategy. 

Desirable Requirements 

• Experience building or contributing todigital twin,synthetic control, ormechanistic-MLhybridmodels in a healthcare or life-sciences setting. 

• Familiarity withmultimodal representation learning, including vision-language models, graph neural networks, or time-series transformers. 

• Priorwork withmulti-omics integration (genomics, transcriptomics, proteomics, single-cell) and pathway-informed modelling. 

• Experience deploying models inregulated environments (GxP, SaMD) and familiarity withmodel interpretability,uncertainty quantification, andfairness frameworks. 

• Exposure tocloud platforms (AWS, Azure, GCP),MLOps tooling, and reproducible research practices (containers, workflow managers, experiment tracking). 

• Experience collaborating withinpharma R&D,clinical development, oracademic medicalcentres. 

Why AstraZeneca 

At AstraZeneca, we are pioneering a new era of scientific discovery wheredata, AI, and human ingenuity converge to redefine what medicine can do. Our AI/ML community spans thousands of scientists and engineers working across the entire value chain—from target discovery to real-world evidence—supported by world-classcompute, curated clinical datasets, and deep therapeuticexpertise. You will have the rare opportunity to see your models move from prototype to production, influencing decisions that shape clinical trials and reach patients globally. 

We offer acompetitive salary, performance bonus,shareprogrammes, comprehensive health benefits, generous parental leave,learning and development budgets, and astrongly hybrid, inclusive working culture. 

Diversity & Inclusion 

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse teamrepresenting 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. All qualified applicants will receive consideration for employment without regard to race,colour, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. 

How to Apply 

Pleasesubmit your CV together with a short cover letter outlining your relevant experience and motivation for the role. Applications will be reviewed on a rolling basis. 

The annual base pay for this position ranges from $72,120.00 - $108,181.20. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans. 

Date Posted

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.