Healthcare Economics Domain Expert, Applied AI

5 trillion in medical expenditures annually and operate on razor-thin 2–5% margins. Despite these stakes, the finance teams behind these organizations are buried in spreadsheets, manual data pulls, and disconnected systems, spending more time finding and cleaning data than actually using it to make decisions. Translucent is changing that.

We're building the AI-native financial platform designed exclusively for healthcare, giving every finance team, department, and service line their own arsenal of AI Agents that run 24/7, understand their specific data, business logic, and workflows. Founded in 2024 and backed by GV, NEA, FPV, and Virtue, we've already been deployed by healthcare organizations managing over $5 billion in combined revenue. The product-market fit is real, the problem is massive, and we're just getting started.

If you want to work at the intersection of AI and one of the most complex, consequential industries in the world, this is the place. Role Overview We are looking for a healthcare economist with deep expertise in revenue cycle management, reimbursement economics, payer-provider dynamics, and the financial operations of enterprise healthcare organizations. We have incredible product-market fit and demand across diverse customer profiles.

Executing on this demand requires someone who understands the full lifecycle of healthcare revenue, from charge capture to final payment, and can translate that expertise into AI-powered systems that help finance teams move from reactive reporting to proactive decision-making.

What You'Ll Do

To facilitate the development of these systems, you will: Develop and deliver subject-matter expertise in healthcare economics and revenue cycle management to support AI research, including reimbursement modeling, denial economics, payer contract analysis, and net revenue optimization Build analytical frameworks for the full revenue cycle: charge capture efficiency, coding accuracy and its financial impact, claims submission and adjudication patterns, denial root cause analysis, and collections performance Model payer-provider economics, including contract rate analysis, fee schedule benchmarking, allowable vs.

Requirements

into technical solutions Build proprietary benchmarks and datasets to evaluate models and AI Agents against real-world healthcare finance tasks, including denial rate analysis, days in A/R trending, net collection rate modeling, and payer performance scoring What You Have 5–10 years of experience in healthcare economics, revenue cycle management, healthcare consulting, or an equivalent function within a health system, medical group, or payer organization Deep understanding of healthcare reimbursement: how providers get paid, what drives variation in payment, and where revenue leaks across the cycle Strong command of revenue cycle KPIs: denial rates, days in A/R, clean claim rates, net collection rates, cost to collect, and how these metrics connect to financial performance Familiarity with Medicare and Medicaid reimbursement methodologies (DRGs, APCs, RBRVS, etc.) and commercial contract structures Experience analyzing claims data, remittanc