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Junior clinical data scientist (crémenes)

Crémenes
Savana
Publicada el 24 marzo
Descripción

SAVANA () is an award-winning, international medical company aiming to accelerate health science by putting into the hands of healthcare providers the power to unlock all of the clinical value embedded within existing Electronic Health Records (EHRs) with Artificial Intelligence and Natural Language Processing.Always ensuring maximum privacy and security.Founded in ****, Savana is an international medical company that has developed a scientific methodology that applies Artificial Intelligence (AI) to unlock all the clinical value embedded within Electronic Health Records' free-text (EHRs).With the largest AI-enabled, multi-language, multi-center research network in the world, Savana generates customized descriptive and predictive, High-quality Deep Real World Evidence research studies.Engineered by doctors for doctors, the company is built following the highest privacy-by-design standards.Savana operantes in more than 160 hospitals, 5 languages, 15 countries and has already improved more than 6 clinical practices with more than 100 employees from 10 nationalities.It constitutes a clinical research ecosystem that aims to advance personalized and precision medicine worldwide.Junior Clinical Data Scientist at SavanaAs an integral part of the Clinical Data Science team, a Clinical Data Scientist must have a strong background in statistics as well as programming.They interact primarily with the Medical Unit team, with whom they must establish effective communication.Nonetheless, their role is also transversal within the organisation, enabling them to contribute their scientific knowledge to any area.Major Accountabilities where this role is involved:Development of Savana Research Study Protocols: drafting the analysis strategy for each study objective, calculation of minimum sample size.Planning and development of Statistical Analysis Plans to fulfill the requirements reflected in Savana Research Study Protocols.Development of new analytic strategies/pipelines to improve

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