McLaren Health Care-posted 3 months ago
Full-time • Entry Level
Flint, MI

The position is responsible for the examination, interpretation, and processing of data to provide insights, solve problems, and support organizational decision-making within provider compensation. Individual may be tasked with internal valuation, benchmarking, modeling, and ad hoc analysis.

  • Acts both independently and in concert with team; consistently exercises discretion and judgment in performing work which is predominantly intellectual and varied in nature.
  • Writes, modifies and executes various production, management, regulatory, customer and ad hoc databases and reports.
  • Provide analytical operations support using a variety of data sources. Analyze and interpret data to provide information for management decisions.
  • Analyze data to identify areas of opportunity that promote operational efficiency and long term organizational success.
  • Identify cost control and cost management issues and recommend actions to resolve.
  • Responsible for reconciliation of provider compensation to contractual terms.
  • Consults/meets with management and/or operating department personnel to determine information requirements and produces specifications for systems projects.
  • Promotes positive internal and external relations by actively seeking and being responsive to customer feedback. Ability to support and participate in continuous quality improvement projects and performance improvement activities.
  • Performs other duties as assigned or when necessary to maintain efficient operations of the department and the organization.
  • Bachelor’s degree in Systems, Accounting, Business, Finance, or related field.
  • One years of prior experience in finance/accounting.
  • Experience in an integrated health system medical group, particularly in Provider Compensation
  • Experience working with Cerner and HPP electronic medical and billing systems
  • Experience in healthcare financial forecasting and analysis.
  • Experience working with large databases, data extraction and analysis.
  • Experience with various data management
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