Senior Real World Evidence Scientist
Do you have expertise in, and passion for, Real World Evidence work? Then AstraZeneca might be the one for you!
AstraZeneca is a leading company in the healthcare industry, with a mission to enrich the lives of others. It’s our business to support balanced living, not only for our patients, but also for our employees. Our benefits program is flexible enough to meet employees’ varying needs, offers valuable choices, and is highly competitive.
Oncology is driven by speed. Here you will be backed by leadership and empowered at every level to prioritize and make bold moves. Be a fearless decision-maker. Speak up and constructively challenge. Powered to take smart risks based on scientific evidence. Here it’s our scale, agility and passion that makes sure we deliver fast, every time.
The Oncology Real World Evidence R&D team is a new group being growing within AstraZeneca. AstraZeneca has a pedigree of experience in Real World Evidence, having developed a coherent strategy to develop and internalize rich data assets the group is now amplifying those investments through a Real World Evidence Data Science capability.
We are looking for MSc/PhD level epidemiologists, bio-statisticians, biomedical data scientists, clinicians/pharmacologists or related fields with a strong desire to learn and expand their skillset into the analysis of Real World Evidence (RWE).
The ideal candidate for this role will have deep understanding of epidemiology and will bring a consistent track record of delivering value through the use of routinely collected data from healthcare settings to provide health analytics and insights in both Public Health, Pharmaceutical Research and Development and Commercial context.
* This role provides coaching, task management and support to Programmers/Statistics/Information Scientists, promoting standard methodology across multiple domains, and/or partner groups.
The AstraZeneca Oncology R&D RWE group provides expert analysis and interpretation of the complex biomedical data captured in electronic health records, claims data, registries, wearables and epidemiological observations.
This important work, which provides a rich window on the complicated realities of patients and diseases, is used to support the drug development process in a variety of ways, including:
- Developing real world cohorts of patients matching clinical trial inclusion exclusion criteria
- Analyzing longitudinal health data to characterize patient journeys and outcomes
- Sifting claims and prescription data for use patterns and to support label expansion
- Building predictive models of patient outcomes
- Identifying patient subtypes (e.g. via biomarkers) for possible therapy development
- Building synthetic and external control arms to support the interpretation of clinical studies
- Development of algorithms for better diagnosis and identification of patients
- Searching for evidence of adverse effects in medical histories
- Using federated networks of electronic health records for patient identification and recruitment
- Using real world evidence to support pragmatic and hybrid trial designs
- Partnering with external organizations to generate bespoke real world datasets
- MSc/PhD in data science or other advanced degree in life sciences with post-doctoral or other training/work in Medical Informatics or related field
- Use of statistical and scripting languages such as R, Python and SQL
- Clinical trials and recruitment, especially the application of synthetic control arms
- Experience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data science
- Demonstrated ability to build long-term relationships with partners at senior levels, understand relevant scientific/business challenges at a deep level and translate into a program of informatics activities to deliver defined value
- Ability to lead & manage multi-disciplinary epidemiological projects
- Strong background of delivering large, cross functional projects
- Experience working in a global organization and delivering global solutions
- Health analytics and data mining of routinely collected healthcare data
- The application of genomics in clinical care or translational medicine
- Health economics and quantitative science such as health outcome modelling
- Data science, machine learning and construction of predictive models
- Clinical data standards, medical terminologies and healthcare ontologies
- Work in a patient care or similar setting, that would allow the candidate to bring medical perspective into real-world evidence generation
- Experience design and implementing pragmatic clinical trials
- Experience in the use of Instant Health Data
At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.
So, what’s next?
- Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.
- Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
Where can I find out more?
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AstraZeneca 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 authorisation and employment eligibility verification requirements.