Top Senior Data & Analytics Jobs in Reno, NV

The Lead Implementation Specialist is responsible for data integration, reporting, and visualization, ensuring compliance, facilitating client support, mentoring, and driving continuous improvement in data processes.

Build, optimize, and maintain web analytics data and reporting. Deliver weekly reports and insights, perform deep-dive analyses, recommend website optimizations, partner with paid digital and email teams, and ensure accurate Adobe Analytics implementations.

Lead and execute applied research on law school access, affordability, and outcomes. Manage and clean data, run advanced statistical analyses, produce tables/visualizations and technical reports, maintain research tools, advise internal and external stakeholders, and present findings at conferences.

Lead scaling of Arbital's AWS/Databricks lakehouse and Spark pipelines, implement actuarial healthcare calculations, own Airflow orchestration and CI/CD, ensure data quality and HIPAA-compliant PHI handling, partner with data scientists to deploy ML models, and set platform architecture and engineering standards.

Design, build, and maintain scalable backend systems and data pipelines to generate point-of-care insights; collaborate with product and engineering stakeholders; mentor junior engineers; ensure solutions are secure, performant, maintainable, and support analytics and unified metrics collection.

Design, build, and deliver a global analytics platform: manage data collection and pipelines, develop visualizations and reports, create semantic models, tune performance, collaborate with IT and business stakeholders, and implement governance for analytics products.

Perform hands-on Epic data conversion activities including CCDA/PAMI ingestion, source-to-target mapping, ETL, data validation, reconciliation, mock conversions, cutover support, troubleshooting, and documentation to ensure accurate migration of clinical and operational data from multiple legacy EMRs into Epic.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Lead measurement strategy for a book of clients using statistical modeling (MMM), incrementality experiments (MMT), and customer analysis. Build insights from large datasets with R, Python, and SQL, present actionable recommendations to clients, mentor analysts, improve measurement processes, and leverage Nova and AI to optimize deliverables and impact business goals.

Design and maintain enterprise revenue-cycle KPIs and dashboards, analyze multi-source RCM datasets, build predictive models, identify process improvements, support audit/compliance, lead stakeholder working groups, author executive deliverables, follow PM best practices, mentor junior analysts, and safeguard PHI/PII under DoD controls.