Healthcare pricing is a mirage. The number on the bill isn’t what anyone actually pays, and the number someone pays is never the “price.” It’s the result of a negotiation no one sees, shaped by contracts no one reads, built on models no one understands.
Yuzu Health is a TPA, which means we’re in the business of turning that mirage into an actual number and paying doctors. But we’re not just dealing with neatly coded, traditionally billed claims. We’re reimbursing pharmacy visits from the OCR of crinkled receipts. We’re giving members pre-loaded debit cards to pay before leaving the waiting room.
That only works if we can decide how much to pay. Not weeks after the visit, but when someone is still choosing where to go.
Most of the industry treats that decision as someone else’s job. Pricing is either handed off to a vendor with some vague proprietary dataset or buried inside a 25 year old network contract. But when you’re paying for care in real time, it’s not a back-office detail. It’s core infrastructure. It affects how care is accessed, how trust is built, and how well the whole system holds together. Getting it right doesn’t mean finding the perfect number. It means designing a way to make fair, fast, and explainable decisions.
You’ll be the first person here focused full-time on pricing data and software. You’ll imagine and build our pricing technology from the ground up:
Design the system that determines how much insurance plans that we operate pay for medical services
Identify where industry-standard logic breaks down and find simpler, more defensible alternatives
Build tools to simulate pricing outcomes and explain decisions to non-technical stakeholders (including members)
Locate and work with datasets to allow us to make real-time decisions with incomplete information
In person in Flatiron NYC office 5 days/week
$140k-$200k + equity
A more statistical/data oriented and less software oriented person is qualified for this role provided they can organize and communicate engineering work to software engineers without subject matter expertise.
You care about the incentives you create and the people they affect
You are comfortable working with meaningful volumes of data and building pipelines and software around it
You’ve worked with messy financial or healthcare data and made it useful
You’re comfortable with ambiguity and laying the groundwork
Bonus: you understand RBP and/or CMS Medicare pricing procedures (or want to)
You want to analyze data without owning an outcome
You’re afraid of shipping a first draft
You’re content accepting things that don’t make sense
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