At AstraZeneca we work together across global boundaries to make an impact and find answers to challenges. We do this with the upmost integrity even in the most difficult situations because we are committed to doing the right thing. We continuously forge partnerships that help pursue world-class medicines in new ways, combining our people’s exceptional skills with those of people from all over the globe. As a Real World Evidence Senior Data Scientist/Data Scientist in Gaithersburg, MD, you’ll play a pivotal role in channeling our scientific capabilities to make a positive impact on changing patients’ lives.
The HEOR team is a group within AstraZeneca’s US Medical Affairs Oncology which is driving the scientific use of Real World Data to accelerate the way patients access innovative medicines. The HEOR team comprises of a core research team divided into four franchises focused on gathering Health Economic and Real World Evidence, to support our products. AstraZeneca has a rich history in Real World Evidence, having developed a coherent strategy to develop and internalize data assets the group is now amplifying those investments through a Real World Data Science capability. Real World Data Scientists who are successful in this role will work on challenging problems, using innovative approaches to accelerate the delivery of Real World Insights and Evidence for key internal and external stakeholders.
The ideal candidate for this role will bring a proven track record of delivering value through the leverage of routinely collected data from healthcare settings to provide health analytics and insights in a range of contexts including Public Health, Pharmaceutical Research and Development and Commercial/ Payer.
The data scientist will collaborate with colleagues in Epidemiology, Statistics and Payer, giving scientific and technical guidance on study design, RW data selection and best practice in RW data utilization.
In addition, they will assist HEOR and Medical colleagues in advancing and shaping the US Medical Affairs functions Real World Science data strategy through the due diligence on new data providers/vendors, informatics support for data acquisitions in the oncology area.
The role will promote best practice in Real World Data Science across multiple domains, and/or stakeholder groups.
Main Duties and Responsibilities:
- Collaborate with HEOR, Medical, Payer and Epidemiology teams to maximise the value derived from large observational research data
- Deliver secondary analyses of data from EMR, claims and primary observational data required by TA RWE strategies
- Support the development of Innovative Value Strategies and selection of optimised contract models for the US market through analysis of RWD
- Provide scientific guidance on the application of Real World Evidence and observational research data to address issues across the Oncology business unit
- Provide technical input, options and directions to strategic decisions made by the HEOR and Medical teams on study design, data partner selection and best practices in RWE data utilization
- Support technical teams to provide access to analytical tools and develop visual analytics to enable self-serving applications for end customers
- Provide clear technical input, options, and direction to strategic decisions on RWE platform and capability build
- Provide support for strategic decisions on AZ Medical Evidence and Observational Research external collaborations in the US.
- Assist in building a capability that becomes a source of sustained competitive advantage for AZ in identifying, acquiring, integrating and mining diverse RW data from multiple geographic and healthcare system sources to support evidence generation and real-world studies
- Evaluate and assess strengths and weaknesses of external RW data sources, and potential partners for advancing the data strategy for specific therapeutic areas
- Maintain a strong insight into the capabilities of potential external partners in RWE, for the US market.
- PhD or MS in data science or other advanced degree in life sciences with post doctoral or other training/work in Medical/Health Informatics or related field
- Expertise in EMR/Health IT, disease registries, and insurance claims databases
- Expertise in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies (ICD9/10/ReadCode)
- Experience in Statistical Analysis Plan (SAP) generation and execution for observational studies
- Experience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data science
- Expertise in methods development and application using statistical languages such as R/Matlab/SAS/SQL/Hadoop/Python
- Experience in advanced visualisation and visual analytics of routinely collected healthcare data
- Experience in real-world evidence and familiarity with health economics/epidemiology, and quantitative science such as health outcome modelling
- Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data
- A history of patient care or equivalent background of working at a patient care setting that allows the candidate to bring medical perspective into real-world evidence generation and observational studies
- Demonstrated ability to build long-term relationships with stakeholders at senior levels, understand relevant scientific/business challenges at a deep level and translate into a programme of informatics activities to deliver defined value
- Ability to lead & manage multi-disciplinary data science projects
- Strong track record of delivering large, cross functional projects
- Experience working in a global organization and delivering global solutions
- Use of Machine Learning, Predictive modelling, and Artificial Intelligence in the generation of hypotheses within Real World Data
Next Steps – Apply today!
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