Top Remote Data & Analytics Jobs

Lead a small analytics team to produce data-driven insights for marketing and media optimization. Mine proprietary datasets, apply statistical methods, forecast KPI impacts, monitor business metrics, and act as liaison between business and technical teams to drive profitable media and client growth.

Analyze high-scale payment funnel and transactional data to identify conversion bottlenecks, design and evaluate A/B tests, define metrics and measurement frameworks, monitor product performance via dashboards, and translate insights into prioritized product recommendations in partnership with Product and Engineering.

Design, build, and maintain petabyte-scale batch and streaming data pipelines and core data infrastructure for robotics foundation model training. Own data models, storage, ingestion, transformation, and orchestration. Standardize pipelines across teleoperation and simulation datasets and collaborate with cross-functional team to support Physical AI development.

Lead mixed-methods research with a quantitative focus: design analytics, run experiments, analyze product usage, build dashboards, enable self-service, support product discovery, and translate findings to influence product strategy.

Maintain and monitor data pipelines that aggregate healthcare claims for the Cost Roll process. Validate and reconcile claim and provider demographic data, troubleshoot data issues, perform data quality checks, and collaborate with stakeholders to ensure reliable downstream financial and clinical systems.

Lead architecture and operations for the end-to-end data lifecycle: pipeline orchestration, dbt projects, cloud warehouse performance, dimensional modeling, data observability, HIPAA controls, and platform governance. Mentor a distributed data engineering team, partner with Analytics and Finance, and prioritize durable platform capabilities that enable BI, experimentation, and AI use cases.

The Manager of Business Analytics - Fraud leads efforts to develop and optimize fraud risk strategies, improve monitoring frameworks, and support product launches through analytical insights on fraud risks.

Design and maintain dashboards and reports, perform deep-dive analyses to identify trends and anomalies, ensure data integrity with engineers and data scientists, automate reporting, and translate complex datasets into clear insights for non-technical stakeholders.

Lead the design and development of data engineering solutions, apply analytical methods for forecasting, build dashboards, and ensure data quality and governance.

The role involves driving the identification of requirements, improving systems processes, developing prototypes, and ensuring usability in product development projects within an AI company.