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Salary
$80k – $130k per year
Location
Remote/Hybrid (Boston, United States)
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 23, 2026. First seen by Alion on Jun 23, 2026.

Overview
Company
Impact
Profile match
Zus is the only shared health data platform designed to accelerate healthcare data interoperability by providing easy-to-use patient data at the point of care via API, embedded components, and direct EHR integrations.

What we're looking for:

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.

As part of our team, you will be focused on...

    Coverage Intelligence

    • 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

    • Operations Partnership

      • 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

      • Tooling & Automation

        • 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

        • Product Feedback Loop

          • 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

You're a good fit because you have...

    • SQL fluency: You write queries naturally and reach for them first when you have a question about data. Experience with BI tools (Looker, Metabase, Tableau, etc.) is a plus

    • Automation instinct: You don't accept manual work as permanent. You're comfortable in Python and curious about AI-assisted workflows - you'd rather build a system than repeat a task

    • Analytical curiosity: You notice when numbers don't add up and you follow the thread. You're comfortable sitting with ambiguous data and forming hypotheses

    • Clear communicator: You can translate a coverage analysis into a crisp, jargon-free narrative for a customer or an executive

    • Healthcare interest: Prior exposure to clinical data formats (FHIR, HL7, C-CDA) or the provider/EMRecosystem is a plus, but a genuine interest in how healthcare data flows is what matters most

Why this role matters...

    Data coverage is one of the most tangible levers for customer value at Zus and right now, the infrastructure for understanding and improving it is still being built. You'll have real ownership over that build: the metrics, the tooling, and the feedback loops that help the network get better over time. The work compounds.

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