Location: Barcelona, Spain (on-site) - 3 days working from the office and 2 days working from home.Job DescriptionAstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases.Oncology is driven by speed. Here you will be backed by leadership and empowered at every level to prioritize and make ambitious moves. Be a daring decision-maker. Speak up and constructively challenge. Powered to take sensible risks based on scientific evidence.The Oncology Real World Evidence R&D team is a new group growing within AstraZeneca. We are looking for quantitative epidemiologists, bioinformaticians, health informaticians, biomedical data scientists, clinicians/pharmacologists, bio-statisticians or related fields with a strong desire to learn and expand their abilities into the analysis of Real World Evidence (RWE).The role holder will be a subject matter expert on the use of Real World Data and its capabilities. The role holder will transform real-world clinical data into concrete insights for clinical development using statistical methods and innovative data visualizations to support decisions.The AstraZeneca Oncology R&D RWE group provides expert analysis and interpretation of complex biomedical data captured in electronic health records, claims data, registries, wearables and epidemiological observations. This important work supports the drug development process in various ways, including:Supporting clinical project teams to understand the benefits of RWD and support them in their clinical designDeveloping close connections with biometrics and clinical teams to develop a strategy for RWD use within a drug development programInteracting with senior stakeholders to ensure the value of RWD is understood and supported within a Research and Development settingAnalyzing longitudinal health data to characterize patient journeys and outcomesSifting claims and prescription data for use patterns and to support label expansionBuilding predictive models of patient outcomesIdentifying patient subtypes (e.g. via biomarkers) for possible therapy developmentBuilding synthetic control arms to support the interpretation of clinical studiesDeveloping algorithms for better diagnosis and identification of patientsSearching for evidence of adverse effects in medical historiesEstimating the number of eligible patients for clinical trials from databases and literatureUsing federated networks of electronic health records for patient identification and recruitmentUsing real world evidence to support pragmatic and hybrid trial designsPartnering with external organizations to generate custom real world datasetsMinimum Qualifications:Master's degree + 5+ years of relevant experienceExperience in supporting a multidisciplinary team build a research objective that can be met with RWDExperience in the use and application of RWD to support clinical decision makingHealth analytics and data mining of routinely collected healthcare dataUse of statistical and scripting languages such as R, Python and SQLClinical trials and recruitment, especially the application of synthetic control armsThe application of genomics in clinical care or translational medicineHealth economics or epidemiology, and quantitative science such as health outcome modellingDesirable Skills:PhD DegreeData science, machine learning and construction of predictive modelsClinical data standards, medical terminologies and healthcare ontologiesWork in a patient care or similar setting, that would allow the candidate to bring medical perspective into real-world evidence generationExperience designing and implementing pragmatic clinical trialsKnowledge of Oncology and Pharmaceutical developmentDate Posted: 24-oct-2024Closing Date: 22-nov-2024AstraZeneca 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 welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.
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