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

The Log Specialist at Dynatrace leads log management initiatives, collaborates with sales, architects data ingestion solutions, and advocates for enhanced log consumption strategies.

The Sr. Analyst in Pricing Analytics drives data-driven strategies for GoodRx by analyzing pricing, collaborating with cross-functional teams, and developing dashboards to support business decisions.

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

The role involves leading Quote-to-Revenue processes, mentoring junior team members, and ensuring quality deliverables in finance systems and billing operations.

Lead encounter data operations: monitor submissions, correct rejected encounters per CMS/DHCS, write SQL queries and ad hoc scripts, generate reconciliation reports, analyze trends and root causes, validate EDI 837 resubmissions, manage relationships with health plans and clearinghouses, update documentation and training, and lead special projects to improve finance-related encounter workflows.

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

Lead client-facing analytics engagements focused on Adobe Analytics and CJA. Drive measurement strategy, implementations, scalable dashboards, and executive insights. Lead and mentor project teams, collaborate cross-functionally, ensure information security and data privacy compliance, and travel as needed to support clients and global teams.

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