Top Remote Data & Analytics Jobs in Spokane, WA

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

The Strategic Insights Lead analyzes healthcare data to shape business strategies, delivers impactful insights, and collaborates with various teams to ensure clarity and actionability in findings.

The Staff Risk Analytics role involves overseeing fraud risk management, developing strategies, leading cross-functional initiatives, and providing real-time analytics in fintech.

Lead analytical projects, develop quantitative models, analyze datasets for insights, and translate findings into business recommendations, primarily supporting client decision-making.

The Head of Data at BetterSleep will own the data function, manage a team, develop data infrastructure, and enhance analytics and measurement strategies to support product and growth initiatives.

The Senior Data Scientist will lead analytics efforts, develop data models, and improve data pipelines to support Thyme Care's mission in oncology care, while collaborating with stakeholders to enhance performance metrics and reporting.

The Data Scientist will enhance statistical models for forecasting, analyze datasets for operational planning, and communicate insights to stakeholders.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.