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Remote Health by SafetyWing


Global health insurance for freelancers & remote workers

Redox


closed

data science

This job post is closed and the position is probably filled. Please do not apply.
At Redox our mission is to enable the frictionless adoption of technology in healthcare. To that end we have enabled a network of healthcare organizations and technology developers to connect through us to improve patient healthcare. Our customers have asked us to help minimize data duplication for various scenarios. An ideal candidate is a data science enthusiast and will solve complex data-related problems, using advanced statistical and machine learning tools, in a real-world setting with product managers and engineers. Candidates should demonstrate strong statistical, mathematical and technical skills, with proven capabilities to transition ideas into fully working projects. In addition, the candidate needs to have a creative and first principles mindset to examine our current processes and help us grow our Data Science muscle at Redox. \n\n\n\n\nWHAT YOU'LL DO:\n\n\n\n\n* Apply advanced statistical and predictive modeling techniques to build, maintain, and improve multiple real-time decision-making systems – from research to production and deployment\n\n* Collaborate on highly technical projects - from redesigning working infrastructures to maintaining and improving our current models and underlying systems to integrating new technologies to the data science workflow\n\n* Enhance data collection procedures to include information that is relevant for building our analytical systems\n\n\n\n\n\n\n\n\n\n\nWHAT WE LOOK FOR:\n\n\n\n\n* Minimum 3-5 years of experience working in data science at a company. \n\n* Experience working with machine learning libraries, for example, Fastai, Numpy, xgboost, sklearn, scipy among others; natural language processing experience is a plus\n\n* Experience with deep learning frameworks (Tensorflow, PyTorch, etc) a plus\n\n* Experience in implementing statistical/machine learning algorithms (parametric and non-parametric models, classification and regression trees, Bayesian models, clustering and dimensionality reduction techniques)\n\n* Background in at least one high level programming language (e.g.,Python, R, Java, Javascript)\n\n\n\n\n\n\n\n\nAbout Redox:\n\nWhat We Do\nHealthcare organizations and technology vendors connect to Redox once, then authorize what data they send to and receive from partners through a centralized hub. Redox's cloud-based platform is vendor and standards agnostic and enables the secure and efficient exchange of healthcare data.\n\nThis approach eradicates the need for point-to-point integrations and accelerates the discovery, adoption, and distribution of patient and provider-facing technology solutions. With hundreds of healthcare organizations and technology vendors exchanging data today, Redox represents the largest interoperable network in healthcare. Learn how you can leverage the Redox platform at www.redoxengine.com.\n\nOther Stuff About Us\nRedox is an EEO company. We fully support the diversity of our team! Here's a recent blog post about our stance on diversity and belonging: Diversity at Redox\n\nWe believe in holding ourselves to a high standard of conduct. Here's how we think about this: Redox Code of Conduct\n\nSuccessful candidates must be eligible to be employed in the US, and must reside in the US.\n\nThank you for your interest in Redox!


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