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 (HAI) Team strives to transform the patient experience and clinical trial process. We will do so by deploying digital solutions to decrease patient burden in clinical trials and in the real world. 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 a Machine Learning Data Scientist to support a diverse range of projects including: developing, optimizing and scaling learning algorithms and models, prototyping applications, building tool and infrastructure to serve and monitor models, providing software design and programming support to research projects. The role will interact with product engineering, digital health platform teams, and research teams, and also work closely with the Digital Health R&D subject matter experts and collaborators to develop novel approaches that support the development of patient and HCP-facing digital products.
- Design, develop, test, deploy and maintain ML infrastructure.
- Optimize model training infrastructure, pipelines, and model/dataset versioning. Perform model training, hyper parameter tuning.
- Release ML or statistical models into production using APIs or on-device inference. Monitor model performance and manage continuous learning pipelines.
- Set up multimodal data pipelines for ingesting and processing text, audio, images, and streaming events.
- Build libraries and frameworks that support web or mobile applications.
- Collaborate in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
- Bachelor's Degree in a quantitative field (computer science, mathematics, statistics, etc.) with industry experience with machine learning infrastructure or a combination of data science/ML experience and Dev Ops experience.
- Extensive experience with programming in Python and experience working with Pytorch and Tensorflow.
- Research or industry experience in Artificial Intelligence, Machine Learning (ML) models, ML infrastructure, Natural Language Processing, Computer Vision or Deep Learning.
- Experience with SQL and NoSQL databases (PostgreSQL, MongoDB, KSQL, etc.)
- AWS or other cloud compute experience including SysOps.
- Experience with ML pipeline orchestration and monitoring (bespoke or with tools such as Apache Airflow or Snowflake)
- Residence: Barcelona
- Advance degree in relevant field
- Experience in building, deploying, and improving ML models and algorithms in real-world products.
- Experience with models for processing language, audio, video and other modalities.
- Experience with implementing numerical methods, multi-objective optimization algorithms, graph modeling.
- Experience with low level languages used for implementing high performance ML code (C, C++, Rust, CUDA, etc.).
- Experience deploying ML models for inference on a phone or other mobile device.
- Advanced machine learning models: transformer-based NLP models, reinforcement learning, GNNs, state-of-the-art timeseries & forecasting models.
- Experience with interactive data visualization.
- Experience within the pharmaceutical industry.
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 recognising their potential. Join us on our journey of building a new kind of organisation 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.So, what’s next!
If you are ready to make a difference - apply today, and we'll make it happen together!
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