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language (Python, C, C++ or Java) and familiarity with scripting languages (bash, Perl). Knowledge of Unix operating system, terminal and bash is a plus. Experience using a compute cluster. Excellent
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policy, economics, statistics, or a related quantitative field Additional Qualifications Strong skills in Stata, R and/or Python and experience analyzing complex data Demonstrated experience working with
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, Python, and SAS or Stata Demonstrated expertise in analysis of claims data Clear scientific writing and communication, an ability to work both independently and in teams, and a track record of publications
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demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must
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scientific, word processing, spreadsheet or statistical software applications or program platforms including R, SAS, Python, and MPlus. Acquires Specialized Training. Attends trainings and skill development
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. Ability to develop clear and complex visualizations Technical Proficiency: Prior experience with SQL, QlikView, MS Power BI, R, or Python is highly preferred. Communication: Exceptional ability to translate
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skills in statistical analysis (e.g., R), computational methods (e.g., NLP methods), programming (e.g., Python), online research tools (e.g., Qualtrics) Strong interpersonal skills and a high level of
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, Python, and SAS or Stata) • Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling, experience with Medicare claims data • Clear scientific writing and
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the Python deep learning software stack, particularly expertise in PyTorch, Numpy, and related packages. Experience handling and processing large and diverse datasets, especially medical texts, journals
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cellular neurophysiology or related fields Experience in patch clamp-based electrophysiological recording from native neurons Expertise in programming with Python and R Experience with programming