Top Healthtech Data & Analytics Jobs in Seattle, WA

Designs and maintains scalable data pipelines and infrastructure, establishes data governance and quality standards, and drives technical decisions across Headway’s data platform. Partners with Product, Engineering, Analytics, Data Science, Infrastructure, Finance, and Insurance Systems to improve architecture, performance, reliability, security, and AI-readiness. Ensures data is complete, traceable, trustworthy, and suitable for powering internal tools and AI-driven insights.

Leads marketing media measurement strategy across Social, TV, Influencer, and Content Marketing. Owns Marketing Mix Modeling, incrementality testing, causal inference, attribution, experimentation, and media effectiveness analysis. Uses SQL and statistical programming to evaluate customer and media data, develop investment recommendations, and communicate findings to executives. Partners cross-functionally with Marketing, Finance, Data Science, Engineering, Product, and agencies while leading analytics talent and remaining hands-on.

Analyze product and healthcare billing data to support product decisions, reporting, experimentation, and claims collection improvements. Build and maintain dashboards, develop scalable datasets, conduct A/B testing, create data visualizations, and communicate actionable insights. Collaborate with product stakeholders, data scientists, and engineers on data modeling, OKRs, data quality, and pipeline reliability for Billing and Payments features.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Build scalable, secure data pipelines, models, platforms, and governance systems that enable AI applications to access trusted enterprise data. Partner with analytics, marketing, and product teams to translate requirements into technical solutions, independently deliver projects through production, and support sensitive-data security and access controls. Preferred experience includes LLM architectures, cloud data platforms, infrastructure as code, regulated environments, and technical leadership.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Build Sailor Health’s foundational data platform from scratch. Responsibilities include developing Snowflake and dbt pipelines integrating EHR, CRM, and communications data; creating data-powered web applications; automating clinical and billing workflows with Python; analyzing therapy transcripts and patient data using AI and machine learning; tracking clinical outcomes; and designing scalable data architectures in collaboration with clinicians, engineers, founders, and other teams.

Analyze healthcare claims and clinical data to build data models, analytical pipelines, predictive and risk-model inputs, dashboards, scorecards, and reusable analytics assets. Translate ambiguous customer and clinical questions into actionable data plans, manage delivery across stakeholders, present findings to customers, maintain quality standards, mentor junior analysts, and contribute to analytics roadmaps, automation, and scalable methodologies.