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

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

Lead pricing analytics for GoodRx Companion subscription: build forecasting and elasticity models, optimize pricing to drive signups and unit economics, create dashboards and reports, analyze fill patterns, and deliver actionable insights to cross-functional stakeholders to improve program performance.

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

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

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

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Lead design and implementation of an enterprise Databricks lakehouse, build scalable batch and streaming pipelines, enforce governance and CI/CD standards, optimize Spark workloads, operationalize ML with MLflow, manage cloud infrastructure and IaC, and mentor data engineering teams.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.