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wellness programs and resources, and much more. Posted Job Title Senior Data Scientist, Wharton Graduate Division Job Profile Title Job Description Summary The Senior Data Scientist - Algorithmic Systems is
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Scientist, Wharton Graduate Division Job Profile Title Job Description Summary The Senior Data Scientist – Algorithmic Systems is a key member of the Data Science team supporting the full-time, Executive, and
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Epic. Exceptional technical writing skills are essential to the success of the candidate. The candidate is expected to be detail oriented; have excellent organizational and time management skills in a
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experts, and translate them into efficient and maintainable code. This requires knowledge in (or the ability to learn) macroeconomics, a good foundation in (optimization) algorithms, and the ability
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Description Job Responsibilities Determination of subject eligibility upon detailed review of medical chart via EPIC; assembling study enrollment packets. Approach all eligible subjects every weekday and obtain
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electronic health records software for clinical documentation and reporting (Epic preferred). Knowledge and experience in developing and implementing policies and procedures. Must be able to work cooperatively
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from specialized human movement datasets. Assist in identifying available datasets, performing data annotation, developing and applying machine learning algorithms for extracting movement and contextual
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maintenance of machine learning algorithms, applications, analysis pipelines, and results reporting methodologies using R and SAS (including R functions and SAS macros for data management and analysis support
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of EPIC preferred but not required. Position contingent upon funding Job Location - City, State Philadelphia, Pennsylvania Department / School Perelman School of Medicine Pay Range $55,000.00 - $75,000.00
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and demonstrates skill in prioritizing competing job duties.- Ability to utilize computer software (Word, Outlook, Excel)- Knowledge of EPIC preferred but not required. Position contingent upon funding