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University of California, Los Angeles | Los Angeles, California | United States | about 22 hours ago
of medical terminology, particularly urology. General knowledge of third party insurances, government programs and other insurance agencies for purposes of assigning financial class codes and obtaining any
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examining how the approach can be effectively supplied to guide field plot placement. The successful applicant will optimize existing code and test and validate the approach on a cloud computing environment
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. The ideal candidate will act as a bridge between business needs and technology solutions, leveraging low-code or no-code platforms to develop solutions that enhance operational efficiency and advance SAO’s
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and procedural policy. This includes guiding students in the project design process, providing design feedback (as needed/requested) to students on best coding practices. The incumbent will also train
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reports. Enters documentation for contracts, receipts, and invoices in appropriate system with minimal errors Reviews documents for mathematical accuracy, proper coding, compliance, and approval as directed
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-facing app creation using both code-based and no-code tools. Collaboration is key, with responsibilities including effective communication across teams and vendors, partnering with users to generate
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JOB DUTIES Description As the Clinical Documentation Integrity Specialist – Medicare Advantage Risk Adjustment, you will be an expert in risk adjustment coding and documentation, working closely
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responsible for planning and organizing necessary tasks to ensure adherence to the study protocol and applicable regulations, such as institutional policy and procedures, FDA Code of Federal Regulations (CFR
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of medical records to evaluate accuracy of codes for medical billing and to ensure that all services have been captured. Applies general knowledge of CMS regulations and third-party payer guidelines to confirm
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 13 days ago
and profile existing research AI workloads to identify performance bottlenecks and portability challenges; and port and optimize complex AI models and scientific code to run efficiently on AMD MI355X