Top Analysis Reporting Jobs in Reno, NV

Conduct local sports and entertainment sponsorship research, identify brands and sponsorship assets, document signage and activations, and submit accurate observations to SponsorUnited’s database. Scouts complete training, communicate progress, manage assignments independently, and may attend approved local events. The six-month internship is remote and assignment-based, with potential in-person venue scouting. Compensation is unpaid, though approved event and venue-access costs may be covered.

Lead the architecture and development of enterprise analytics models, dbt transformation pipelines, semantic layers, and BI datasets. Apply dimensional modeling, data governance, quality testing, observability, and performance optimization to deliver trusted business data. Partner with executives and cross-functional teams, standardize metrics, improve legacy workflows, support AI/ML integrations, and mentor engineers. Own key domain models and contribute to the analytics platform roadmap as a technical leader.

Owns enterprise customer experience research and measurement strategy across patient and provider journeys. Leads Voice of Customer, NPS, CSAT, CES, qualitative and quantitative research, competitive benchmarking, journey metrics, governance, dashboard requirements and insight synthesis. Presents evidence-based recommendations to executives, influences investment decisions, establishes research standards, and coordinates vendors, budgets and cross-functional initiatives while maintaining privacy, compliance and data-governance standards.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Evaluates and compares chatbot responses against business requirements and quality criteria. Gathers requirements, documents functional specifications, analyzes workflows and data, creates reports and dashboards, supports testing and UAT, tracks project risks and KPIs, and presents evidence-based findings. Collaborates with technical teams and stakeholders to improve AI output quality while maintaining evaluation consistency and meeting deadlines.

Develops dashboards, data models, reports, and analytical solutions that transform raw data into actionable business insights. Partners with stakeholders, provides technical guidance, documents architectures and processes, troubleshoots analytics solutions, and communicates findings to technical and non-technical audiences. Requires advanced Spotfire, SQL, business intelligence, and data analytics expertise, with knowledge of Databricks, Power BI, Python, R, Salesforce, and modern data architecture.

Build and maintain scalable batch and incremental data pipelines using Python, SQL, and Snowflake. Develop data warehouse models, transformations, automation, quality checks, lineage, alerting, and performance optimizations. Collaborate with analysts, data scientists, and application teams to deliver trusted datasets, while documenting pipelines, schemas, and data contracts.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Designs and maintains a scalable data platform supporting analytics, machine learning, and AI workloads. Builds tooling for reliable data pipelines, semantic layers, data agents, LLM applications, and evaluation systems. Ensures data quality, availability, observability, and reliability while establishing modeling, testing, and platform best practices. Collaborates with Data Science and Product Engineering, leads solutions from design through implementation, and contributes individually in a fast-paced startup environment.

Own the technical design and operation of Palmetto’s governed data platform. Build trusted data products, semantic models, ingestion and transformation pipelines, secure access interfaces, and agent-ready data services. Establish governance, masking, authorization, observability, CI/CD, and audit readiness. Partner with finance, operations, product, and engineering teams while mentoring engineers and setting cross-team technical direction.