Transform healthcare by leading high-value workstreams within Actuarial and Analytics Solutions (AAS) department, supporting medical economics, payment integrity, and finance areas
Requirements
- Experience with machine learning algorithms, statistical techniques, data interpretation methodologies, and deploying Predictive Models
- Familiarity of software for data analysis and modeling; specifically: Python, SQL, Tableau, statistical software (R, SAS etc)
- Proficiency working with modern data & analytics technologies and solutions on cloud platform (Snowflake preferred)
- Familiarity with working in an Agile Environment and partnering closely with IT
- Deep and broad understanding of health care delivery system and health plan operations
- Experience with claims data
- Knowledge of Medical Economics, Trend Management, Pricing, Forecasting, Provider Payment Methodologies, and industry benchmarks
Responsibilities
- Lead the research, design, and implementation of data science solutions to support current/future business needs
- Anticipate and provide strategies/solutions to complex data problems or trends
- Evaluate and design new approaches and methodologies to solve business problems or improve efficiency
- Utilize statistical techniques to execute on advanced measurements of messy/noisy data
- Produce meaningful observations and recommendations through synthesizing data from internal and external sources
- Drive the design, building, and launching of new data models and data pipelines
- Manage the delivery of high impact dashboards and data visualizations
Other
- Minimum of five years of health care experience in analysis, design, development and delivery of data solutions
- BA/BS required; MS, MPH, PhD in relevant field considered in lieu of work experience
- High school degree or equivalent required
- Ability to effectively communicate with all levels of the organization
- Strong customer focus and ability to work effectively in matrix environment
