Top Remote Data & Analytics Jobs in Seattle, WA

The Credit Bureau Business Analyst will manage bureau execution and analysis, support product onboarding and compliance controls, and drive data quality improvements through data analysis and cross-functional collaboration.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.

Maintain and improve eligibility and claims data feeds, analyze feed performance and errors, troubleshoot discrepancies, work with external feed providers to map and test integrations, and help improve internal tools, documentation, and processes.

Lead analytics work translating complex healthcare data into decision-ready insights. Own KPI definitions, Snowflake data marts with dbt, executive dashboards in QuickSight, and cross-functional analyses to inform strategy, product, and operations.

The Senior Healthcare Analyst will analyze healthcare data, provide insights to improve clinical programs, and collaborate with multidisciplinary teams to drive program effectiveness and optimize patient outcomes.

The Analyst II will leverage data analytics to derive insights, optimize credit strategies, and collaborate with cross-functional teams including Machine Learning and Engineering.

The Sr. Data Analyst will deliver actionable insights to stakeholders, develop predictive models, and support data-driven growth by analyzing diverse datasets.

The Market Risk Analyst will monitor SBL lines of credit, assess market risks, manage collateral, develop risk models, and prepare reports.

Support GitLab's go-to-market planning, target setting, compensation design, analytics, and capacity planning for revenue growth.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.