Manager Risk Adjustment Analytics

The Manager Risk Adjustment Analytics works to align risk adjustment data with organizational initiatives. This position will work closely with Risk Adjustment leadership to help tie the bid, budget, and operational outcomes of the Risk Adjustment campaigns in the Generations Advantage program. This position will partner with operational leadership to solve business problems and find patterns and insights within structured and unstructured data to effectively communicate and drive discussions with GA operational leadership in tactical and strategic business decisions for the program.

Key Outcomes:

• Engage GA Leadership and Data Analytic staff in problem solving and process improvement activities to ensure efficient use of resources, and optimal, accurate revenue capture
• Propose and assist GA Leadership in implementing analytic strategies and solutions that challenge and enhance current operations
• Provide expert analysis of large, complex, multi-dimensional datasets with a variety of tools
• Create processes and mentor GA Leadership and Data Analytics staff on best practices that ensure the quality of data output for submissions to and from vendors and CMS
• Provide consultation to all levels of management relating to appropriate use of organizational data assets as they relate to Risk Adjustment activities, RA Revenue, and RAF Scores
• Develop reporting and analytics to support Martin’s Point strategic and tactical needs specific to Revenue, HEDIS, Stars, Quality, and other related activities
• Effectively package the presentation of reporting and analyses to various audiences using a variety of data visualization tools
• Work with output from purchased software packages and external data sources to inform GA Leadership in business decision making in the areas of:
  • Developing assessments of future risk (both financial and clinical) for presentation to various audiences
  • Developing risk-adjusted clinical and financial performance profiling
  • Incorporating HEDIS, Stars, and Quality related data into various analytic projects
• Work with Data and Analytics team to develop and document common methodologies, definitions, and databases for analytic reporting, ensuring accuracy, eliminating duplication of efforts, and providing a forum for sharing ideas and creative problem solving for integration of data systems and continuous process improvement
• Research new data sources and perform data discovery as required
• Develop knowledge and understanding of business processes at MPHC
• Manage internal and external department relations involving projects and operations

Required License(s) and/or Certification(s):

• None

Skills/Knowledge/Competencies (Behaviors):  

• Demonstrates an understanding of and alignment with Martin’s Point Values
• Ability to lead change and assist in the development of strategies that support and align with Martin’s Point values, mission, goals, and objectives
• Knowledge of the health care industry, data warehousing concepts, applications, and toolsets
• Demonstrated interpersonal, communications, operational, team building, and quality improvement skills
• Effective team leader and builder including ability to establish accountability within the team
• Data manipulation skills using current state tools (SQL, Access)
• Effective presentation of reporting and analytic results using a variety of tools
• Understanding of CPT and ICD-9 coding as well as medical terminology
• Knowledge of standard health care metrics for payer and provider reporting
• Ability to interpret and scope customer requirements
• Data Visualization Tools, such as WEAVE, Tableau
• BI Tools - such as Cognos or Business Objects
• Accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS, or SAS. Has experience with BI tools such as Tableau, Cognos, WEAVE, Microstrategy
• Familiar with relational databases as you are with Hadoop-based data mining frameworks
• Familiar with SQL, Python, Java and/or C/C++
• Possess a deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms
• Can solve complex analytical problems related to Risk Adjustment and other related operational activities using quantitative approaches with a blend of analytical, geospatial, mathematical, and technical skills