Evolent Health has built a world-class team to help forward-looking health plans and providers succeed under new value-based care payment models. Risk adjustment and quality measurement are some of the most significant quantitative challenges facing these innovators. Evolent’s team of experts in risk adjustment & quality does it all – from data analytics & advanced modeling (e.g. predictive models & artificial intelligence), to designing, presenting, and implementing industry-leading solutions with our partners. The Associate Director, Risk & Quality Analytics will be working with this highly-advanced team of actuaries and data scientists to develop and maintain risk adjustment & quality improvement analytic capabilities.
Extract, transform, analyze, and summarize claims, member encounter, and other health data to answer business questions and provide exploratory analyses.
Develop and provide subject matter expertise in risk adjustment & quality measurement for various lines of business
Quantify and forecast program financial and operational returns related to risk adjustment & quality
Work in a collaborative environment with other innovative professionals to develop best-in-breed risk adjustment & quality reporting solutions
Explain highly technical details to non-technical audiences and develop supportive materials to educate executives and partners on capabilities
Collaborate with other departments to deliver scalable solutions across disparate skillsets
Develop reporting capabilities to measure and forecast risk scores & quality metrics, monitor suspecting model performance, and identify areas of improvement
Monitor industry trends to influence future enhancements
Use cutting edge tools & techniques to produce insights to improve our processes and research to share internally and externally
The Experience You’ll Need (Required):
Bachelor’s degree in public health, computer science, statistics, actuarial science, economics, health science, health administration, or related field
Strong technical abilities with advanced data and analytics tools and programming languages, with at least 1 year of experience in Python or R and SQL.
Willingness to gain an understanding of Medicare, Medicaid, and ACO risk adjustment and quality rating systems
Collaborative working style with the ability to work across different departments and personalities as well as comfort in a highly matrixed and ambiguous environment
Ability to handle multiple projects and timelines effectively
3-5 years of experience in a health analytics, quantitative analyst, or software engineering / programming role
Ability to understand and apply highly technical specifications to healthcare datasets
MS office and proficient programming skills – SAS, SQL, and/or Python. Experience with writing data Extract-Transform-Load (ETL) scripts in SQL or any other programming language with emphasis on loading & processing data files (CSV, Excel, Text, etc.).
Strong verbal & written skills and excellent communication & presentation skills. Comfortable presenting complex analyses
Collaborative working style with the ability to work across different organizations and personalities as well as comfort in a highly matrixed environment
Ability to multitask, prioritize, adapt to change, work well under pressure in an entrepreneurial environment, meet deadlines, and manage a project from start to finish
Finishing Touches (Preferred):
Master’s degree in epidemiology, biostatistics, public health, data science, operations research, or related field
Familiarity with NCQA/HEDIS, CMS, or PQA quality measures
Progress toward Actuarial Credentials
Experience with predictive modeling or machine learning
Familiarity with Risk Scoring Models (e.g., CMS-HCC, HHS-HCC, CDPS)
Experience with healthcare data sources (claims, billing data, eligibility, etc.) & detailed knowledge of CPT/HCPCS/ICD9/ICD10