At AstraZeneca, we work together to deliver innovative medicines to patients across global boundaries. We make an impact and find solutions to challenges. We do this with integrity, even in the most difficult situations, because we are committed to doing the right thing.
The Digital Health Oncology R&D; Human-centered AI and Machine Learning Team strives to transform the patient experience and clinical trial process. We will do so by deploying digital solutions to clinical trials and in the real world to decrease patient burden. The approach the team takes will incorporate clinical trial data, Real World Evidence (RWE) data, clinical free text, medical imaging, Patient Reported Outcomes (PROs), and device data to define new digital approaches to addressing the pressing problems across the AZ R&D; portfolio.
The team is looking for an Associate Director of Data Science to specialize in the development of innovative machine learning methods focused on multi-modal datasets including clinical trial data, RWE, imaging data, and other biomedical data sources to address patient burden. Examples of projects the team works on include:
Machine learning models for developing digital biomarkersDigital therapeuticsComputer vision diagnostics and clinical decision support toolsApproaches to quantitatively analyze wearable dataLinking of medical imaging data with 'omics and longitudinal outcomes to identify and/or validate new drug targets- Drives projects with hands-on data science, analysis, or mathematical modeling.
- Delivers sophisticated data science solutions to AstraZeneca projects, selecting analytical methods with appropriate complexity given a clinical or business challenge.
- Engages technical and non-technical collaborators within the wider organization to frame complex challenges, structure analytical solutions, and communicate results.
- Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
- Reviews working practices and ensures non-compliant processes are raised.
- Collaborates in a multidisciplinary environment with world-leading clinicians, data scientists, biological experts, statisticians, and IT professionals.
EssentialB.Sc. in a relevant field (such as mathematics, computer science, engineering).Demonstrated an outstanding track-record of industry experience with the desired data science methodologies.Practical software development skills in standard data science tools: Python, Agile, Code versioning (bitbucket/git), UNIX skills, familiarity working in cloud environments (AWS preferred).End-to-end experience leading collaborative data science projects in an industry setting.ML Ops experience: model tracking, model governance, multiple models in different production contexts.Experience developing machine learning first products including time-series analysis, forecasting, behavioral analysis.Knowledge of a range of mathematical and statistical modeling techniques and drive to continue to learn and develop these skills.Communication, business analysis, and consultancy; ability to present compelling cases to stakeholders and operate dynamically to identify solutions.Residence: Barcelona.DesirableAdvanced degree in rigorous quantitative science (such as mathematics, computer science, engineering) or M.B.A. with analytics experience in the industry.Experience within the pharmaceutical industry.Advanced statistical and machine learning models such as hierarchical mixed Bayesian models, transformer-based NLP models, reinforcement learning, deep learning models that span CNN/RNN/LSTM, GNNs, constrained optimization, state-of-the-art time series & forecasting models.Why AstraZeneca?At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognizing their potential. Join us on our journey of building a new kind of organization 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. Interested? Come and join our journey.
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