Top Data & Analytics Jobs in Las Vegas, NV

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

Design and maintain enterprise data architecture and lakehouse solutions. Lead data migration, integration, governance, and BI enablement. Define strategy, implement pipelines, ensure data quality, security, and provide technical leadership and mentoring.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

The Senior Data Engineer will design and operate data systems, optimize data pipelines, and enhance AI workflows for legal operations. Responsibilities include data modeling, implementing governance standards, collaborating with cross-functional teams, and mentoring junior engineers.

Extract, clean, and transform data from multiple sources; build and optimize dashboards and reports; perform root cause analysis and statistical modeling; collaborate with leaders and Data Engineers to translate business needs; streamline data workflows and perform database migrations and schema mapping.

Design, build, and maintain dbt models, ELT pipelines, Looker explores and visualizations. Drive analytics strategy, data discoverability, observability, lineage, and security. Mentor engineers, collaborate cross-functionally, apply software engineering best practices, and integrate AI to scale data products and self-service BI.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Lead customer-facing analytics: build dashboards, reports, and POCs that demonstrate ROI and utilization trends for healthcare provider data. Collaborate with data science and engineering on advanced models, assess and integrate new data sources, ensure data quality, and support presales and executive-facing storytelling.

Perform quantitative analysis and model development support within an economic capital team. Clean and explore large datasets, run basic diagnostics, build visualizations, and assist in validating predictive and ML models using Python/R/SAS and spreadsheet tools. Help integrate AI-generated code and agentic tools under manager supervision.