Top Remote Artificial Intelligence Data & Analytics Jobs

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Collect, clean, and analyze data to support business decisions; build dashboards and reports; identify trends and insights; and present findings to stakeholders. Maintain attention to detail and apply problem-solving to derive actionable recommendations.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

As a French Fact-Checking Annotator, you will evaluate responses for factual accuracy, apply guidelines, identify misinformation, and provide structured annotations while maintaining high quality and detail.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Design, build, and maintain automation workflows and data pipelines across admissions, education, career services, and billing. Create BI dashboards, ensure data accuracy, manage lightweight databases (e.g., Supabase), and support cross-functional teams to improve operational efficiency and scalability.