Top Remote Data & Analytics Jobs in Seattle, WA

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Lead data steward for Personal Lines Product, Pricing, and Underwriting domains. Define and maintain a data roadmap, translate plans into actionable epics, govern data policy and classification, and coordinate stakeholders to modernize systems (streaming, data vault, warehousing) and enable a unified insurance platform. Advise Agile squads and collaborate with technical teams to implement durable, compliant data solutions.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Partner with Sales, RevOps, Finance, and Data Engineering to convert CRM and pipeline data into actionable insights. Build and maintain pipeline and forecasting reports, dashboards, and metrics; identify risks and opportunities; improve data quality and reporting reliability; triage analytics requests; and embed AI tooling into analytics workflows to accelerate output and ensure analytical rigor.

Partner with Customer Success and CS Ops to build post-sales analytics: customer health scoring, renewal and renewal pipeline reporting, billing and support signal analysis, and expansion/upsell dashboards. Own dashboard ecosystem, translate stakeholder requests into scalable reporting, collaborate with Finance and Data Engineering, and leverage AI tools to accelerate analytic workflows and maintain data quality for retention and expansion decision-making.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Monitor and verify accuracy of live e-sports game data feeds in real time, identify and resolve discrepancies, cross-check multiple sources, escalate issues, and collaborate to streamline processes. Maintain knowledge of schedules, rosters, rule changes, and key metrics to ensure contextual data accuracy throughout the season.

Lead design and execution of Toast's enterprise data governance: define strategy, build governance frameworks, policies, business glossary, Data Governance Council, ensure compliance (GDPR/CCPA/SOC2/PCI-DSS), run maturity assessments, enable data literacy, and grow the governance team to drive adoption across domains.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead design and governance of enterprise-scale data architecture (warehouses, lakehouses, streaming). Define standards for data quality, lineage, observability, and AI-enabled workflows. Mentor engineers, serve as technical escalation, and translate business needs into long-term data architecture and governance strategies.