Top Data & Analytics Jobs

Leads healthcare analytics service delivery across Medicare, Medicaid, and Commercial programs. Designs analytic models, dashboards, reports, and predictive solutions; translates complex data into client-ready insights; guides data governance and management practices; and promotes AI, machine learning, generative AI, and automation to improve reporting efficiency. Partners with clients, analysts, developers, subject matter experts, and AI teams to analyze claims, enrollment, provider, and member data and support value-based payment initiatives.

Analyze healthcare risk adjustment and health plan data across Medicare, Medicaid, and ACA Commercial programs. Build and maintain reliable data solutions using SQL, Python, ETL processes, databases, Tableau, Power BI, and Excel. Investigate application, data, system, and workflow issues, identify root causes, recommend corrective actions, and collaborate with technical teams to resolve problems.

Manage incentive-system data intake, processing, reporting, output, archival, and quality assurance. Investigate discrepancies, perform root-cause analysis, improve process flows, automate recurring activities, support system troubleshooting, and maintain data integrity. Collaborate with stakeholders, handle data-processing inquiries, document procedures, and apply SQL and Python to analysis and automation. Varicent experience is optional.

Manage advanced operational and client reporting, metrics, dashboards, data models, and business analysis. Analyze complex datasets, identify trends and performance drivers, resolve data-quality issues, and develop automated AI-driven insights. The role partners with business and analytics teams, presents findings to stakeholders, supports strategic decisions, and continuously improves reporting capabilities and processes.

Build workforce demand forecasts and capacity plans, analyze operational performance metrics, identify trends and service risks, and present staffing requirements to business partners. Collaborate across workforce planning and operations teams, validate plan accuracy, lead process improvements, mentor peers, support planning initiatives, and champion workforce tools.

Analyzes workforce data, forecasts staffing needs, develops and maintains workforce models, and provides operational recommendations to improve member satisfaction. The role addresses complex workforce management issues, supports planning and capacity meetings, evaluates processes and defects, and communicates findings to stakeholders. It requires experience with workforce management software, forecasting, project leadership, systems administration or reporting, and call center technologies.

Designs scalable, secure data architectures; performs proof-of-concepts; troubleshoots technology and environment issues; develops Azure cloud applications; and migrates BDPass data pipelines to Azure. The role requires cloud platform expertise, data security and privacy knowledge, programming in Python, Java, and SQL, big data technologies, data warehousing, modeling, data management, software development, and agile methodologies.

Designs scalable, secure cloud data architectures; performs technology proofs of concept, troubleshoots across environments, and migrates BDPass data pipelines to Azure. The role requires expertise in AWS and Azure, data engineering programming, big data technologies, data warehousing, modeling, security, software development, and agile practices, along with strong problem-solving, communication, and collaboration skills.

Design, build, test, deploy, and maintain scalable Azure-based data pipelines and integrations for healthcare analytics. Lead data acquisition, ETL/ELT transformations, data quality detection and remediation, monitoring, documentation, and collaboration with analytics teams to enable BI and advanced analytics while ensuring security and reliability.

Develop and maintain batch and streaming data pipelines supporting analytics and enterprise reporting. Use Python, Spark, Scala, Azure Data Factory, Databricks, Kafka, and cloud storage technologies. Support ETL/ELT, data warehousing, monitoring, incident resolution, security remediation, upgrades, testing, and production stability. Collaborate with cross-functional teams, document solutions, and participate in knowledge transfer while learning enterprise healthcare data systems.