Top Remote Analysis Reporting Jobs in Las Vegas, NV

Build and lead Ashley’s consumer insights capability, including research roadmaps, custom qualitative and quantitative studies, insights repositories, prioritization processes, and executive-ready storytelling. Translate consumer, retail, marketplace, feedback, and business data into actionable recommendations for product, marketing, merchandising, pricing, and growth decisions. Influence cross-functional stakeholders, develop AI-enabled synthesis workflows, and manage one direct report while operating resourcefully with imperfect data.

Own end-to-end product analytics: define questions and success metrics, run A/B tests, build dashboards and reusable SQL/Python analyses, investigate performance changes, and collaborate with Product, ML, and Data teams to inform product decisions.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.