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

The Senior Data Analyst will lead analytics projects, translate complex data into insights, and support product strategies across various teams, ensuring data-driven decision making.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.

The Data Engineer will lead data projects, collaborate with stakeholders, develop data transformations, and maintain data quality for business needs.

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

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

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.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead a unified analytics organization for Marketing and Product, define shared metrics and measurement frameworks, deliver executive-ready insights, build forecasting and experimentation programs, partner with engineering and privacy teams, and hire and mentor multi-layer analytics teams to drive product adoption and business outcomes.

Design, develop, and maintain forecasting and optimization models for contact forecasting, headcount planning, staffing and budget. Partner cross-functionally to produce data-driven recommendations, present to leadership, and mentor forecasting analysts.