Top Remote Data & Analytics Jobs

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.

The Senior Analyst will support product engineering efforts by analyzing digital solutions, enhancing user experiences, and collaborating across teams to deliver insights and improvements.

Lead and grow a software engineering team focused on RISC-V software ecosystem, collaborating with teams to establish RISC-V as the standard.

Own reconciliation and validation of client billing across internal systems, build repeatable data-quality checks and documentation, support Client Group with reporting and dashboards, investigate discrepancies, and drive process improvements and automation to reduce billing friction.

Design, develop, and optimize SQL-based data solutions and ETL pipelines in Microsoft SQL Server. Ensure data accuracy, performance tuning, validation, and documentation. Partner with delivery, engineering, and client teams, support production systems, participate in code reviews, and drive process improvements with minimal oversight.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Design, develop, and optimize Microsoft SQL Server data solutions and ETL pipelines. Build complex T-SQL queries, stored procedures, views, and performance optimizations. Ensure data quality, translate requirements into technical implementations, document logic, support production, and collaborate with delivery, engineering, and client teams.

Design, build, deploy, and support production data pipelines and enterprise data solutions in Databricks and GCP. Develop data models and layered architectures, ensure data quality, security, and governance, integrate multiple sources, and support analytics, AI/ML, reporting, and operational decision-making while collaborating with technical teams and federal stakeholders.

Produce and maintain recurring category and retailer reports, validate and reconcile data, support ad-hoc analysis and promotion/assortment reviews, and collaborate with Sales and Marketing to surface shopper-focused insights and improve reporting processes.