Analyst, Payer Strategy

recoursehealth.com•San Francisco, CA

1d•Remote

About The Position

Figure out how payers behave, then turn that into offers that win. A federal arbitration system called Independent Dispute Resolution, or IDR, now determines billions of dollars in healthcare payments each year. Providers win the vast majority of disputes, yet most eligible claims are never filed. The process is manual, fragmented, and resource-intensive, and most providers don't have the infrastructure to pursue what they're owed. The No Surprises Act created the framework, and the market already exists. Today it runs on spreadsheets, consultants, and static playbooks. We're building the first intelligent system designed to operate inside it. IDR is a repeated game. The same payers and the same arbitrators show up again and again. Whoever learns fastest from outcomes builds a compounding edge that nobody can copy. This role is how we learn. Every dispute produces signal. Which claims won, at what offer multiple, against which payer, in front of which arbitrator, with which evidence. Most of the industry throws that signal away. We want to capture all of it and turn it into a system that gets sharper every month. The hard part is that the signal is noisy and the sample is small at first. Payers change behavior. Arbitrators rotate. Regulations shift under you. You need enough statistical honesty to know when a pattern is real and enough operator judgment to act before you have perfect data. You'll spend your time in claims data, decision letters, and remittance files, looking for the thing nobody has noticed yet. Then you'll turn it into a rule the system can apply.

Requirements

3+ years in analytics, data science, strategy, or a similarly quantitative role
Strong SQL. You pull your own data and you don't wait for someone else to do it
Comfort with Python or R for anything SQL can't handle
Hands-on fluency with AI tooling. You have used it to accelerate real analytical work, not just tried the demos
Clear written communication. Your analysis has to change what other people do, which means they have to understand it
A preference for small teams and early-stage chaos over mature org charts
Sound judgment, analytical depth, and ownership mindset are required.

Nice To Haves

Healthcare data experience is a strong plus: claims, 835s, EOBs, CPT and diagnosis coding, payer contracting
Experience with the No Surprises Act, IDR, arbitration, payer contracting, or out-of-network claims.

Responsibilities

Analyze outcomes across every dispute we file: win rate, offer multiple, recovery, time to resolution
Build payer profiles that explain how each insurer behaves and where they can be pushed
Run loss analysis on every dispute we don't win, and turn the reason into a rule
Model offer strategy: what to submit, against which payer, for which CPT context, and why
Work with CMS public use file data to benchmark our performance against the whole market
Partner with engineering to encode what you learn into the product, so the system applies it automatically
Build the dashboards and reporting the whole team runs on

Benefits

Institutional backing
Shared platform team spanning engineering, strategy, design, and back-office
Early access to large provider systems
Funded, validated opportunity with real customers and real data
Opportunity to be the best work of your career
Opportunity to ship real things, with people who raised your game, on something that mattered
Clear thinking, high ownership, intellectual honesty, and direct communication valued
Operations, product, and engineering operate as one pod
Machines do machine work, humans do their best work
Paid vacations
Supportive culture