Top Remote Senior Level Data & Analytics Jobs in Los Angeles, CA

Lead product analytics function, manage a team of analysts, drive data-informed decisions, and partner with Product and Engineering teams.

Lead design and build of a cloud-based data platform for simulation outputs: architect AWS data warehouse and ingestion, transform high-volume telemetry into trusted datasets, establish schemas/data contracts, enable replay/comparison, support analytics/AI, and hire and mentor a data engineering team.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Brand & GTM Analytics Manager leads measurement and reporting for brand marketing, collaborates with cross-functional teams, and analyzes initiatives to drive growth and influence decision-making.

The Senior Product Analyst at Toast collaborates with various teams to analyze data, develop measurement frameworks, and enhance product development through insights, dashboards, and reporting tools.

The Market Risk Analyst will monitor SBL lines of credit, assess market risks, manage collateral, develop risk models, and prepare reports.

Lead a Planning & Analytics team for Midwest retail accounts (Target, Best Buy, Kohl's), deliver insights from POS and syndicated data, pressure-test forecasts, build dashboards, drive promotional and pricing analysis, collaborate with cross-functional teams, and present recommendations to senior leadership to grow market share.

As a Senior Analyst, you'll gather and analyze requirements, implement process improvements, manage financial reporting in Workday, and mentor junior analysts.

Lead product-focused risk analytics to improve payments risk outcomes and seller experience. Design and analyze A/B tests, build models and monitoring, partner with Product and Engineering, and translate insights into product and risk improvements.

Lead data science for payments risk by designing experiments, modeling customer behavior, evaluating risk controls, building metrics and dashboards, and partnering cross-functionally to inform product and risk strategy.