Manager, Risk Adjustment Informatics

CVS Health•Washington, DC

1d•$66,330 - $145,860

About The Position

The Revenue Integrity Informatics department at Aetna ensures accurate and compliant risk score capture via data-driven member/provider engagement and retrospective documentation review initiatives. Within Revenue Integrity Informatics, the Valuation Analytics team uses complex data from multiple data sources to track and report on the financial impact of Risk Adjustment initiatives to stakeholders in program/vendor management, and to assist/enable other analytics teams across informatics and actuarial to accurately and efficiently incorporate RI valuation data into their work. This individual contributor. Manager, Risk Adjustment Informatics will be responsible for developing and supporting analytical, reporting, and data management solutions to quantify the financial and risk score impact of Medicare Advantage risk adjustment interventions and support enterprise decision-making.

Requirements

5+ years of experience in healthcare analytics, data management, data engineering, reporting, or business analytics.
3+ years of experience writing complex SQL queries in cloud-based environments such as Big Query, Databricks, AWS, or similar platforms.
Experience developing and supporting automated reporting, production processes, or data pipelines.
Experienced using GitHub or other source control tools to manage code repositories and version control
Experience working with healthcare claims, enrollment, provider, diagnosis, finance, or risk adjustment data.
Demonstrated ability to communicate technical concepts to both technical and non-technical stakeholders.

Nice To Haves

Experience leading or supporting large-scale modernization and migration initiatives.
3+ years of experience with Python, SAS, or equivalent data engineering/analytics programming languages.
Experience with Medicare Advantage and/or ACA Risk Adjustment.
Experience implementing, maintaining, validating, or reconciling CMS risk adjustment models.
Experience developing and maintaining member-level healthcare datasets or other large-scale healthcare data assets.
Experience with healthcare valuation, medical economics, risk adjustment economics, provider performance measurement, or healthcare finance concepts.
Master's degree or equivalent advanced analytical experience

Responsibilities

Develop, enhance, automate, and maintain standardized monthly program evaluation and KPI reporting using claims, enrollment, diagnosis, provider, and risk adjustment data from multiple enterprise and government data sources.
Develop and maintain member-level risk adjustment datasets, risk score files, and support analytic outputs for Medicare Advantage and ACA programs.
Maintain, validate, enhance, and document CMS risk adjustment models in Python and Databricks, including annual model updates, hierarchy logic, interaction logic, reconciliation activities, and support for downstream analytics users.
Design, develop, and maintain cloud-based datasets, automated data pipelines, and analytical infrastructure within Google Cloud Platform (BigQuery), Databricks, AWS, and Python environments.
Develop, automate, and streamline processes used to share risk adjustment valuation data, reporting outputs, and reference datasets with business and reporting partners.
Lead and support migration of analytic processes and data assets from SAS to cloud-based solutions, including BigQuery, Databricks, AWS, and Python.
Monitor data quality across source systems, reference datasets, and reporting outputs; identify root causes of issues and partner with stakeholders to implement sustainable solutions.
Own and support recurring monthly and ad hoc production processes, including monitoring, quality control, troubleshooting, issue resolution, and process documentation.
Maintain and improve reference datasets, business rules, and metadata supporting risk adjustment models, valuation processes, KPI reporting, and program analytics.
Partner with Informatics, Revenue Integrity, Actuarial, PMO, Data Engineering, and other stakeholders to gather requirements and deliver scalable analytical solutions.
Research and respond to complex ad hoc questions related to risk adjustment program performance, valuation methodologies, and healthcare financial outcomes.