Top Remote Data & Analytics Jobs in Los Angeles, CA

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Perform healthcare economic analyses by building databases, statistical models, SQL/Python queries, and dashboards. Translate complex clinical and financial data into actionable recommendations, present findings to stakeholders, and support data governance and performance metric development.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

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

Lead contact center analytics by analyzing large datasets, building predictive models, ensuring data quality, and creating dashboards. Collaborate with cross-functional teams, identify AI/automation opportunities, present insights to executives, and maintain data privacy and repeatable reporting processes to improve customer experience and operational efficiency.

Support the Data Team with ad hoc analyses, SQL queries, dashboard maintenance, data quality, and AI-assisted analytics workflows. Prepare reports and presentations, document metrics and workflows, triage data requests via Jira, and help maintain data integrity across BI tools for internal stakeholders.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

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

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Lead Retail GTM analytics and territory operations: build reporting, automate workflows, design territory models, manage data quality/enrichment, and deliver decision-support tools across Salesforce, Snowflake, and Sigma to scale sales coverage and drive growth.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.