Top Data & Analytics Jobs in Reno, NV

As a Staff Analytics Engineer, you'll lead analytics architecture, ensure data quality, collaborate with stakeholders, and drive AI-powered data insights for business decision-making.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Pricing Analyst will analyze market data, assist in RFP processes, collaborate with the Business Development team, and provide detailed recommendations to improve pricing strategies and customer solutions.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Serve as a strategic client-facing advisor for Zeta Data Cloud solutions: demo products, support audience curation, audit accounts, identify intelligence-driven opportunities, train client teams, contribute client feedback to the product roadmap, and support RFPs to drive adoption and growth for agency partners.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Design and automate partner-facing reporting systems, transform complex healthcare data into clear insights, present findings to external stakeholders, support partner success, and collaborate cross-functionally to scale analytics workflows and uncover operational and clinical trends.

Design, build, and operate end-to-end data pipelines and curated compliance datasets powering transaction monitoring, KYC/EDD, and screening. Ensure data quality, lineage, and audit readiness; partner with Compliance and Engineering to improve detection signal quality, define metrics, and deliver repeatable reporting and measurement frameworks for control effectiveness.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.