Responsibilities: Review business requirements and define parameters of more complex analytic projects (i.e. linear models, Tableau visualizations) for customers across the enterprise. The analyst will settle deliverables and deadlines with the customer, beginning to use negotiation and creativity in consultation with management wherever necessary. Research and investigate key business problems through quantitative analyses of healthcare cost and quality data. Manage all aspects of data preparation, analysis, and interpretation in order to meet customer deliverable. Translates highly complex concepts and conclusions in ways that can be understood by a variety of audiences. Compiles complex data sets and simplify tailor according to audience delivering analyses to. Evaluates and processes raw data for user friendly and provides actionable insight (visual and otherwise) to end users. Recommends to leadership advanced analytic models and/or research that financially impact pricing, cost containment, quality, marketing and risk management functions. Develops large, complex advanced analytic models and performs data mining functions to identify trends in the data and/or opportunities for improved outcomes, as appropriate. Demonstrates keen judgment on involved and complex assignments; devises methods and procedures to meet unusual conditions and makes original contributions to the solution of very difficult problems. Provides consultation, complex performance analysis, and coaching expertise to team member around methods of continuous quality improvement. Fosters a culture of continuous improvement that includes the use of performance data to understand health care cost and utilization trends, clinical and condition management analysis, health care cost containment, data quality measurement, and predictive modeling. Improves visual analytics throughout the organization.

Education: Bachelors degree required or 12 years of relevant experience in lieu of degree.

Experience: Minimum of 7 years of experience using statistical concepts and tools. Ability to create, develop/validate models independently. Demonstrates advanced statistical capabilities, data mining, forecasting and predictive modeling skills, and/or actuarial techniques. Demonstrated skills in quality principles especially root cause analysis and problem solving. Demonstrated business and technical problem-solving skills. Advanced analytic software programming proficiency required Extensive experience in analytic tools required (i.e. SAS, Tableau, or others). Experience required in any of the following market leading data & analytic tools but not limited to: SAS, Snowflake, Python, R, Alation, Informatica or similar.