Top Entry Level Data & Analytics Jobs in Las Vegas, NV

As a Data Operations Analyst, you will maintain and enhance Charge Integrity SaaS by utilizing SQL and data analysis to solve complex revenue cycle problems and ensure accurate charge capture.

The Data Entry position requires inputting, updating, and managing data efficiently across various systems, ensuring accuracy and reliability.

As an AI Data Annotation Specialist, you will annotate, label, and curate data for machine learning models, ensuring quality and collaboration with a global team.

The Associate Mathematician creates math models for online and mobile gaming, collaborating with teams to ensure accuracy and compliance, while gathering game statistics.

The Data Entry Specialist manages invoices and payments, ensuring accurate data processing and maintaining records while supporting basic administrative tasks.

The role involves collaborating with business units, facilitating project coordination, resource planning, documenting requirements, and supporting the IT intake process to enhance project delivery and stakeholder satisfaction.

As a Jr. Sales Commission Analyst, you will calculate commission payments, prepare statements, resolve discrepancies, and ensure compliance with SOX controls while maintaining data accuracy.

The Solutions Analyst delivers reporting and operational outputs, analyzes datasets, resolves issues, maintains solution components, and collaborates with teams to improve efficiency.

Build and maintain data marts, materialized views, and pipelines in an AWS Aurora PostgreSQL environment. Integrate data with downstream BI platforms (MicroStrategy), design/optimize workflows for analytics and reporting, monitor pipeline health and data quality, and support federal data security compliance (FISMA/NIST 800-53). Collaborate with engineering and product teams to enable data-driven features.

Collect, validate, and maintain market data across asset classes; perform statistical analysis and modeling; ensure data accuracy through QA; troubleshoot discrepancies; produce reports, dashboards, and recommendations; partner with stakeholders to improve data models and analytics practices.