Senior Data Analyst

Cotiviti is hiring a Senior Data Analyst to manage healthcare data implementations, production, quality, and security. The role analyzes healthcare data, validates it against client requirements, troubleshoots data and mapping issues, and coordinates with customers and data vendors to resolve issues.

Responsibilities:

• Manage data implementations, data production, data quality, and data security
• Perform data analysis of various areas of the data operations function, including reviewing raw data files and assessing data quality within the deliverables
• Facilitate discussions with healthcare data carriers to manage data intake
• Ensure all client data requirements are discussed and confirmed
• Perform data quality checks verifying that data provided is consistent with the requirements to build Healthcare Data Warehouse
• Perform data analysis, data mining and identify root cause of issues using SQL
• Use SQL to write queries to analyze the data
• Analyze all content in the data to ensure that it matches layout and expected valid values, including healthcare eligibility, medical, and pharmacy claims
• Analyze the quality, completeness, and validity of the data for mapping
• Troubleshoot the data based on the results and determine where issues are either with the data or the mapping required for proprietary engine
• Outreach to the customer or the data vendor for corrections or clarifications of the data
• Analyze trends in the data to determine if analytical value has changed and needs to be addressed

Requirements:

• a bachelor's degree or foreign equivalent degree in Computer Science, Information Technology, Information Systems, or related field and 5 years of data warehouse operations experience with healthcare enrollment, medical claims, and drug claims data
• a master's or foreign equivalent degree and 2 years of experience as stated
• 2 years with data analysis, data manipulation using database and spreadsheet applications, extraction and querying skills, non-traditional healthcare data types (including health and wellness, workforce productivity, and EMR), using SQL and TOAD to analyze diverse data sets, analyzing raw data and disseminating results, SSMS, Control-M, Excel, and Jira