Interoperability Operations Analyst

Every customer on the Zus network should have access to the most comprehensive clinical data possible and should understand exactly what they have. As Interoperability Operations Analyst, you'll build the metrics, intelligence, and tooling that make that possible. You'll dig into where coverage is strong and where it's thin, surface the reasons why, and partner with support and solutions teams to close the gaps. When the right fix is a query, you'll write it. When it's an automated workflow, you'll build it.

This is a role for someone who is equally comfortable in a SQL editor and a Python script, gets genuinely curious about unexplained patterns in data, and is excited about using AI tools to work faster and smarter. You'll sit at the intersection of data, operations, and product. Your insights will shape how the network grows and how we serve our customers.

• Build and maintain the metrics and dashboards that track clinical data coverage across the Zus network — by geography, network, data type, and customer

• Identify coverage gaps and anomalies, investigate root causes, and communicate findings clearly to customers and internal stakeholders

• Deliver the regular coverage intelligence that helps every customer understand the depth and breadth of their data — and what's driving any gaps

• Work closely with support and solutions teams to translate coverage findings into operational actions — escalations, network outreach, configuration changes

• Develop and maintain playbooks for recurring coverage issues, turning one-off investigations into repeatable processes

• Contribute to onboarding quality by flagging patterns in new participant data that suggest connectivity or configuration problems

• Build internal tools, scripts, and automated workflows that reduce manual analysis and surface insights faster

• Experiment with AI tools (including Claude) and BI platforms to accelerate how the team operates

• Partner with engineering and product to ensure the systems we rely on generate the signals we need

• Translate operational data into product requirements — if a coverage gap is systematic, you'll articulate why it's a product problem and what solving it would require

• Partner with UX and engineering to shape internal and customer-facing experiences that make coverage intelligence intuitive and actionable