Senior Health Data Scientist

Hire location: Cambridge (UK), Gothenburg (SWE) or Gaithersburg (US)
Competitive salary and Benefits
Be empowered to be innovative and creative where difference is valued
Join a place built on innovation and creativity. Where different views and perspectives are encouraged and valued.
An environment that champions inclusion, and teams that reflect the diversity of the communities that we serve.
It propels each of us forward, harnessing our differences to unlock challenges and bring new solutions. Unleash your curiosity and entrepreneurial spirit to uncover new insights that challenge conventions.
Here we are forever pushing the boundaries as we feel comfortable spotting opportunities, making quick decisions and taking sensible risks
The AI and Analytics team within Astrazeneca’s R&D Data Science and AI group is where great things happen in applying sophisticated algorithms and techniques to some of the hardest problems in the discovery and development of new medicines.
The team demonstrates a blend of scientific, problem solving, and quantitative skills to develop and deliver innovative methods addressing critical problems in Astrazeneca’s R&D environment.
Our team of data scientists & informaticians work right next to our other scientists, allowing them to be close to the questions that matter and work on a broad range of the most promising opportunities quickly.
As a Senior Health Data Scientist, you will be part of a rapidly growing team of Healthcare and Visual Analytics expert focusing on analysing and manipulating routinely collected patient-level data from healthcare settings to generate insights that brings innovative medicines to patients faster.
In this role, you will use patient-level databases including claims, EMR, and registry data to develop innovative data science solutions across multiple therapeutic areas (Respiratory, Cardiovascular, Renal and Metabolism) in clinical drug development.
To achieve this, you will scout new technologies/methods/data assets and work in a highly multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
You will deal with a flexible and varied portfolio of challenges that could include – but are not limited to:
Understanding the patient journey in real world data to optimize patient treatment pathways
Working with drug project teams to find the right sites/investigators in which to run a clinical trial
Researching and developing Machine learning models on multi-modal data to identify digital biomarkers further our understanding of disease
Developing advanced visualisation and visual analytics of routinely collected healthcare data

Accountabilities
Utilises Real World Data (EHR, Claims, Registry & observational data) to support multi-functional projects in R&D and develops advanced data science/informatics solutions across multiple therapeutic areas (Respiratory, Cardiovascular, Renal and Metabolism).
Develops novel analytics solutions where off-the-shelf methodologies do not fit.
Work multi-functionally with multiple partners across R&D to deliver innovative scientific solutions to enable drug projects to optimally utilise large observational datasets and support critical business decisions
Collaborates with the Healthcare and Visual Analytics team to provide technical input to strategic decisions on RWE data strategy, platforms and capability build
Develops working practices to ensure that work is delivered to robust quality standards
Ensures own work is compliant within Clinical Development
Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.

Essential
BSc or MSc in a Life Science, Computer Science or equivalent experience
Disease/therapy area and/or biological sciences domain knowledge
Demonstrated experience in method development and application using statistical languages (such as R, Julia or python) and database languages (e.g. SQL)
Experience in EMR/Health IT, disease registries, and insurance claims databases
Knowledge of clinically relevant public and commercial Real world data assets
Superb communication skills with the ability to work with others to achieve objectives
A passion to apply advance analytics/machine learning to tackle difficult problems in drug development using Real world Data

Desirable
PhD in a Life Science or Computer Science preferred
Expertise with clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies
Use of Machine Learning and Artificial Intelligence in the generation of hypotheses from patient level data
In-depth experience of working in a global organization with complex/geographical context
Strong track record of delivering and managing multi-disciplinary informatics projects
Multiple published papers and/or patents, contribution to external open source projects
Experience in advanced visualisation and visual analytics of routinely collected clinical/healthcare data