Top Data & Analytics Jobs in Las Vegas, NV

The Fraud Analyst monitors transactions for suspicious activity, uses fraud detection tools, documents findings, communicates with clients, and supports the Risk & Compliance team.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Lead data-focused business analysis: elicit and document requirements, model data and processes (As-Is/To-Be), design data flows, support integrations, migrations, EDW/reporting decisions, mentor team members, and drive data governance and cataloguing across enterprise systems.

General application to Cardamom's talent pipeline for roles across Epic analytics, data & analytics, project/product management, and internal functions. Candidates can submit for Epic analyst, data engineering, data science, interoperability, BI, software development, and entry-level roles (Madison local). Talent team reviews submissions and contacts matches for current or upcoming openings.

Lead Southern California risk, actuarial, and analytics strategy for employee benefits. Serve as market-facing advisor, drive client retention and growth, oversee advanced modeling (funding, stop-loss, forecasting), lead analytics team, scale delivery, and partner with national centers of excellence to align tools and execution.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Perform sponsorship valuations through research, data modeling, analysis, and client presentations. Maintain valuation database, surface insights, refine methodology, and support strategy projects to inform sponsorship proposals and renewals.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Serve as the bridge between business stakeholders and development for internal data initiatives. Own intake, discovery, and requirements documentation for analytics, BI, and reporting. Write user stories, acceptance criteria, data definitions, and reporting logic. Maintain a prioritized backlog, support stakeholder validation of prototypes, participate in agile ceremonies, and resolve requirement gaps and risks to ensure development can execute independently.