Top Analytics Jobs in Reno, NV

Lead development of provider data products and ML-based decision support, manage provider data quality, collaborate across teams to build provider-facing analytics, and establish MLOps standards and governance.

Lead design and optimization of analytics products and Tableau dashboards, manage and tune reporting data pipelines (Redshift/ETL), implement performance best practices, collaborate cross-functionally, and drive automation and AI opportunities to improve reporting and analytics for healthcare customers.

Design and deliver HR analytics and AI-forward solutions: perform quantitative and qualitative analyses across the employee lifecycle, build datasets/ETL and visualizations, maintain analytics products, monitor metrics, create executive briefings, and partner with IT and HR stakeholders to drive insights and decision-making.

Oversee the development and maintenance of credit risk models, ensure compliance, validate performance, and manage a team of analysts.

Lead people analytics to deliver executive dashboards, decision-focused analyses, and enterprise people insights. Partner with Talent leaders to translate data into actions, improve measurement validity, and maintain core organization-health metrics. Hands-on role shaping dashboards, narratives, and repeatable insights to drive leadership decisions.

Lead the data organization to define data strategy, build scalable cloud-native pipelines, enable self-service analytics, drive AI/ML initiatives, and manage a multidisciplinary team to inform product, clinical, and business decisions.

Develop and deliver accurate Property operational reports and interactive dashboards, automate and modernize BI processes, analyze complex data to identify trends, and present actionable insights to stakeholders and senior leadership.

Lead advanced analytics for the Host App, performing complex quantitative analysis, experimentation, causal inference, metric design, and reporting. Partner with cross-functional teams to drive product decisions, build data pipelines and analytical tools, and present insights to senior leadership to optimize host and guest experiences.

Hands-on technical lead designing and delivering secure, scalable Azure analytics solutions. Lead solution architecture, guide implementation, mentor engineers, advise on Power BI architecture and governance, and support delivery, consulting, and reuseable asset creation.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Drive marketing performance measurement and attribution by building dashboards, standardizing campaign tracking across HubSpot and Salesforce, running funnel and cohort analyses, ensuring data integrity, and delivering executive reporting to connect marketing activity to pipeline and revenue.

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.

The Director Analyst will oversee the procure to pay lifecycle, master data management, and procurement data analytics, ensuring integrity and optimizing operations.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Design and maintain ETL pipelines and graph data models to ingest security telemetry into an AWS Neptune knowledge graph, enable ML-driven threat detection, optimize query performance, ensure data quality and compliance, and document workflows.

The Manufacturing Analytics Engineer will manage the analytics pipeline, transforming operational data from OT systems into actionable insights for decision-making, while collaborating with Engineering, IT, and Operations.

Design, implement, and optimize data systems for analytics and care coordination, collaborate with teams, and automate reporting processes.

The Director of Analytics will lead the analytics strategy and operations for a top-grossing mobile app, driving data-driven decision-making and insights.

As an Analytics Manager, you'll build dashboards, provide strategic insights, and create a standard data language across teams to enable data-informed decisions.

The role involves executing SEO analysis and testing, managing experiments, translating results into recommendations, and monitoring performance metrics for clients.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Partner with cross-functional teams to analyze large healthcare datasets, build models and dashboards, and surface insights to reduce medical waste. Scope, run, and present analyses, monitor performance metrics, and support initiatives to improve financial and utilization outcomes.

Lead and grow a Locations Analytics team while performing hands-on product analytics, experimentation, causal inference, and geospatial analyses. Partner with Product, Engineering, Design, Data Science, and Marketing to define KPIs, run A/B tests, build reporting and dashboards, and present strategic insights to senior leadership to drive location-based product decisions.

Lead and scale Arcadia's Data & Analytics engineering organization, define multi-year data platform architecture (Snowflake-based), drive platform governance and cross-organizational adoption, optimize large-scale data processing, and align data investments with business goals while building high-performing teams.