Top Healthtech Data & Analytics Jobs

Build AI agents and data acquisition systems, evaluate dataset quality, define quality KPIs, and improve data processes. Partner with product teams to deploy data into customer-facing products and acquire datasets from third parties, including coordinating vendors and contracts. The role requires organizing multiple projects, structuring analyses, communicating tradeoffs, and using data to support investment decisions and customer outcomes.

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.

The Quantitative Methodologist will design statistically rigorous studies, apply advanced analytics, interpret results, ensure quality, and communicate insights to clients.

Build and operate data platform services, APIs, SDKs, schemas, validation tools, event-driven pipelines, and reverse ETL workflows. Improve Kafka-based data delivery, schema evolution, observability, lineage, access controls, privacy, and compliance. Partner with engineering, analytics, data science, security, and infrastructure teams to create reliable, self-service data workflows. Operate AWS services, infrastructure as code, monitoring, alerting, and incident response.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Build data and semantic models, documentation, context, and evaluations that improve conversational analytics powered by LLMs. Embed with stakeholder teams to understand analyst workflows and business needs, then develop self-service tooling and standardized analytic frameworks. Train non-data stakeholders on effective data and LLM usage, create reusable training materials, maintain evaluation processes, and track conversational analytics accuracy. Requires strong SQL, dbt modeling, BI, communication, teaching, problem-solving, and project ownership skills.

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.

Design and maintain billing data systems that reconcile patient engagement data, codify auditable billing logic in BigQuery SQL, automate data cleanup with Python or Google Sheets scripting, and generate accurate, version-controlled invoice files. Investigate mismatches and edge cases, document workflows, and collaborate with Finance, Sales, Engineering, and Product to improve billing inputs and processes.

Build and operate production-grade ELT pipelines from Benchling, Salesforce, and third-party systems into Snowflake using dbt. Own ingestion, transformation, warehouse, BI, governance, monitoring, testing, access controls, privacy, cost, and performance. Partner with AI engineering to provide trusted data for internal AI applications and agentic workflows, contribute to warehouse and metrics-layer architecture, and translate cross-functional stakeholder needs into scalable data solutions.

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.