Top Remote Senior Level Business Intelligence (BI) Jobs in Los Angeles, CA

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

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 Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

The Senior Product Analyst collaborates with Product Managers to analyze data, identify metrics, and provide recommendations to shape product strategy and improve customer experience.

Help new Dynatrace customers adopt Digital Experience capabilities (Synthetic Monitoring, RUM, Session Replay). Perform data-driven analysis, create concise enablement and investigation deliverables, prioritize customer onboarding activities, drive usage expansion, and collaborate with account teams while communicating findings to technical and business stakeholders.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.