Support the clean data transfer between Evolent and its customers in the Performance Suite where Evolent does not pay claims.
Support the design of data transfer protocols during client onboarding and implementation, and refinement efforts on an ongoing basis.
Develop models to evaluate data quality on a regular basis to uncover irregularities in data submitted from clients and work cross-functionally to identify the root cause.
Apply post-pay audit and payment integrity methods and techniques to ensure claims were paid according to policy
Coordinate with internal teams to ensure clean and consistent tracking of Evolent’s covered membership and claims
Support the design of standardized processes, templates, and collateral for key client-facing financial activities
Create models to assist in financial scope reconciliation efforts.
Identify potential risks and opportunities related to partner data, enabling leadership to better resource solutions, negotiate contractual terms, or settlements.
Perform ad hoc client-specific analyses to support strategic decision-making
Requirements
Bachelor’s degree, preferably with a quantitative major (e.g. actuarial, statistics, operations research, mathematics, economics) or healthcare focus (health administration, epidemiology, public health, biology)
1-3 years of professional experience in claims-based healthcare analytics with a payer, provider, clinical vendor, managed care, or related healthcare consulting entity
Ability to communicate clearly with diverse stakeholders to solve problems; ability to translate between business needs and analytical needs
Exceptionally strong analytical abilities, with track record of identifying and communicating insights from quantitative and qualitative data
Advanced or higher proficiency in SQL or SAS database/statistical programming languages and Microsoft Excel
Experience using data visualization software (s) to package analytical insights (Power BI, Tableau, or similar)
Experience in data mining, advanced/ statistical analysis, and data manipulation
Familiarity with healthcare reimbursement methodologies and calculations such as DRGs, Revenue Codes, CPT Codes, RVUs, bundled payments, etc.
Master’s Degree, especially with a quantitative focus (e.g. data science, machine learning, statistics, mathematics, computer science, or engineering)
Preferred
Working knowledge of healthcare claims; specifically, differences between institutional vs professional billing and various sites of care/service
Preferred.
Familiarity with value-based care and utilization management
Preferred.
Understanding data systems and critical thinking skills to solve new problems and adapt to changes in data architecture
Preferred.
Tech Stack
SQL
Tableau
Benefits
comprehensive benefits (including health insurance benefits)