Director, Risk Adjustment Analytics

  • 36750
  • Health - Actuarial
  • |
  • Virginia, United States
  • |
  • Feb 7, 2020
Insurance
RESPONSIBILITIES
  • Manage the calculation and forecasting of risk scores as well as the projection of revenue changes due to risk adjustment.
  • Remain current with annual changes to national and state risk adjustment methodologies and payment parameters; communicate anticipated changes in risk adjustment and how they will affect future revenue.
  • Analyze and present relevant data to inform decisions related to entering risk-based relationships with payers managing risk.
  • Conduct analyses and develop reports to measure risk adjustment operations performance; collaborate with the data science team to identify actionable opportunities to gain operational efficiencies.
  • Support actuarial and finance teams to ensure risk-based reporting needs are satisfied for bidding, rate setting, and revenue projections.
  • Research and prepare evaluations on a variety of complex and diverse projects/problems related to risk adjustment.
  • Communicate results and analyses to internal and external stakeholders.
  • Lead, manage, and mentor analytical staff.
QUALIFICATIONS
  • Bachelor’s Degree.
  • 5-10 years of professional experience in an analytics role at a health plan/payer/insurer, healthcare analytics firm, consulting firm, or hospital system.
  • Deep understanding of risk scoring models and risk adjustment in healthcare.
  • Experience working with healthcare data & detailed knowledge of CPT/HCPCS/ICD9/ICD10.
  • Proven ability to approach complex problems and design, execute, and communicate data-driven solutions.
  • Data manipulation and analysis using SAS, SQL, Python, or other relational databases.
  • Motivation and a strong desire to focus on the complex challenge of risk adjustment in healthcare, develop our team, and contribute to industry thought leadership.
  • Preferred:
  • Graduate degree with a quantitative, healthcare, or technical focus.
  • Actuarial Credentials.
  • Prior employment or consulting experience with Medicaid MCOs.
  • Experience interpreting state Medicaid agency rate setting documentation.
  • Experience with predictive modeling or machine learning.
  • Exceptional Presentation Skills.