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.

The Senior Data Scientist will lead care gap analyses and HCP segmentation strategies using real-world data, mentor team members, and communicate insights to support medical affairs.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

Lead digital measurement strategy for web and digital marketing. Build and maintain dashboards, integrate multi-platform data, perform tagging QA, run A/B test analyses, and deliver insights to optimize campaign effectiveness, UX, and ROAS.

This role oversees the design and evolution of finance reporting solutions using Power BI, collaborating with global finance teams to create scalable analytics and insights.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

Design and implement scalable go-to-market intelligence workflows and automation. Define business requirements for reports and dashboards, partner with Product and Analytics, improve Data Cloud tool adoption, document processes, support integrations, and deliver automation-aligned pre-sales and client-facing materials.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.