Top Senior Analysis Reporting Jobs in Richmond, VA

Identify, develop, and deploy automated cost-saving audits using complex SQL against claims data. Build and maintain financial and ad-hoc reports, run medical record review and administrative hold concepts, lead cross-functional discussions, train teammates on SQL, triage operational tasks (Salesforce, audit letters, reimbursements), and partner with data/engineering to resolve data issues affecting payment integrity.

Lead a data science team to develop insights from autonomous vehicle data, create scalable platforms for data access, and collaborate with cross-functional teams on performance measures.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The role involves leading e-commerce strategies, conducting analysis and A/B testing, collaborating across teams to optimize performance, and translating insights into actionable plans for clients.

The Data Operations Lead oversees the data operations lifecycle, ensuring data quality and reliability, managing teams, and communicating operational status to leadership.

The Senior Data Engineer will design, implement, and optimize scalable data solutions, working with data pipelines and collaborating with cross-functional teams in healthcare.

This role involves leading Reltio-based Master Data Management (MDM) implementations, defining architecture, establishing governance, and collaborating with teams to create solutions across multiple domains.

The Senior Statistical Programmer Consultant will manage programming tasks for clinical trials, oversee deliverables, and validate datasets while ensuring compliance with industry standards.

The Data Insights Manager uncovers insights from data, builds dashboards, collaborates across teams, and drives data-driven decisions to improve business outcomes.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.