Data Analytics Manager - Risk Adjustment (Hybrid)

CareFirst•Baltimore, MD

1d•Hybrid

About The Position

This position leads the analysis, reporting, and performance monitoring activities that support the organization's Risk Adjustment programs. The role is responsible for directing the development of trusted data assets, producing actionable reporting and insights, and leveraging advanced analytics to improve program outcomes through collaboration with clinical, operational, financial, and technology teams. Responsibilities include oversight of key performance metrics, risk score forecasting, member and provider targeting strategies, dashboard and reporting solutions, CMS, HHS, and MDH reconciliation activities, and ad hoc analyses to identify opportunities for enhanced program performance and operational efficiency. The ideal candidate will possess a strong understanding of Medicare Advantage, ACA, and Medicaid risk adjustment methodologies, along with a commitment to data governance, compliance, and analytical excellence. Individual will organize the technology, processes and financial resources necessary to address the current and future analytics needs of the business. Provides thought leadership and acts as a subject matter expert in the designing and recommending of appropriate analytical approaches and methodologies. Provides management responsibility into data-driven insights that inform the business's strategic direction. This role requires candidates to be located in the Maryland, Washington, DC, or Northern Virginia (DMV) area who are willing and able to work in a hybrid model. The incumbent will be expected to work a portion of their week from home and at least two days a week at a CareFirst location based on business needs and work activities/deliverables that week.

Requirements

Bachelor's Degree in Computer Science, Information Systems or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.
5 years Progressive experience relating to data analytics/data analysis
1 year Supervisory experience or demonstrated progressive experience.
Strong quantitative and qualitative skills.
Knowledge and understanding of analytical tools, such as SAS, Excel, SQL.
Excellent communication skills both written and verbal.
Ability to train others.
Must be able to meet established deadlines and handle multiple customer service demands from internal and external customers, within set expectations for service excellence.
Must be able to effectively communicate and provide positive customer service to every internal and external customer, including customers who may be demanding or otherwise challenging.
Must be eligible to work in the U.S. without Sponsorship

Nice To Haves

Data Management\Certified Analytics Professional (CAP) or Data Management\MapR Certified Data Analyst
Master's Degree.
Conceptual data and cloud architecture - understands major native data components in Azure and/or AWS and there relationships and use cases.
Mastery of relational database theory include SQL and at least one major RDBMS.
Well versed in Big Data scenarios and applications.
Experience with multiple analytics delivery tools, methods, and platforms including PowerBI, Fabric, SSMS, and/or Python.
Understanding of Advanced Analytics use cases and the applications of AI/ML for predictive analytics.

Responsibilities

Manage a team with a focus on the development of analytics capabilities across the company, including self-service capabilities through technology implementation, best practices and training.
Ensure team members serve as a trusted advisor to clients on analytics and data.
Interpret statistical analyses and help clients derive meaning from them.
Develop and deliver presentations and reports of analytic findings
Develop hypotheses and research questions to address clients' needs.
Conduct a wide range of quantitative, qualitative, and mixed-methods analyses to develop required reporting.
Develop analytic frameworks and select appropriate analytic methods needed for all deliverables.
Partner with stakeholders to understand data requirements and with internal and/or external resources to develop tools and services such as segmentation, modeling, dashboard development, decision aids, and business case analysis to support the Risk Adjustment Team.
Uses and creates multiple data sets to create reports and data presentations, and eventually creating data dashboards, for leadership and managerial use.