Top Senior Data & Analytics Jobs in Reno, NV

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

Deliver end-to-end healthcare data migration: analyze source systems, develop SQL queries and transformation logic, validate and reconcile converted data, collaborate with clients and teams, and use AI-assisted tools to improve delivery.

Lead the architecture and development of CareDx's enterprise BI ecosystem. Own Power BI modeling, DAX optimization, governance (RLS, deployment pipelines), and self-service enablement. Collaborate with data engineering to build scalable Databricks/Delta Lake/PySpark pipelines, leverage Microsoft Fabric and Lakehouse architecture, mentor BI developers, translate business needs into analytics solutions, and drive BI performance and reliability.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

Lead advanced analytics and predictive modeling for readiness-based spares and sustainment decisions. Translate business problems into analytical frameworks, build predictive/diagnostic models, document data pipelines, mentor junior analysts, and collaborate with engineering and program stakeholders to support Navy and Department of War programs.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Own and build audit-ready data architecture, ETL pipelines, and validations to support internal audit. Maintain inventories, playbooks, and catalogs; assess downstream impacts of schema changes; implement automated data quality checks and monitoring; and translate audit/business requirements into technical specifications for stakeholders.

Partner with GTM leaders to turn large datasets into actionable insight, build dashboards and forecasting models, analyze pipeline/retention/productivity, and implement automation and AI-enabled workflows to improve revenue performance and GTM operations.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.