Senior Real World Evidence Scientist
AstraZeneca
Senior Real World Evidence ScientistBarcelona, SpainAbout AstrazenecaAstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies.Business areaOncology is driven by speed. Here you will be backed by leadership and empowered at every level to prioritise and make ambitious moves. Be a daring decision-maker. Speak up and constructively challenge. Powered to take sensible 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.What you will DoWe 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 abilities 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 sophisticated 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:Analysing longitudinal health data to characterise patient journeys and outcomes across multiple modalities (genomics, clinical, imaging, etc)Sifting 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 and external control arms to support the interpretation of clinical studiesDevelopment of algorithms for better diagnosis and identification of patientsSearching for evidence of adverse effects in medical historiesUsing federated networks of electronic health records for patient identification and recruitmentUsing real world evidence to support pragmatic and hybrid trial designsPartnering with external organisations to generate custom real-world datasetsRequirementsMasters Degree in relevant field (Ph.D. would be preferred)Relevant experienceUse of statistical and scripting languages such as R, Python and SQLClinical trials and recruitment, especially the application of synthetic control armsExperience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data scienceDemonstrated ability to build long-term relationships with partners at senior levels, understand relevant scientific/business challenges at a deep level and translate into a programme of informatics activities to deliver defined valueAbility to lead & manage multi-disciplinary epidemiological projectsStrong background of delivering large, cross functional projectsExperience working in a global organisation and delivering global solutionsDesirable SkillsHealth analytics and data mining of routinely collected healthcare dataThe application of genomics in clinical care or translational medicineHealth economics and quantitative science such as health outcome modellingData 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 design and implementing pragmatic clinical trialsDate Posted 09-abr-2024Closing DateAstraZeneca 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 authorization and employment eligibility verification requirements.
Barcelona
Wed, 10 Apr 2024 23:31:22 GMT
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