Subject Matter Expert, Pharmacy & Healthcare Supply Chain

ROLE DETAILS • Full-Time • Office Location — New York City (preferred) WHY TRANSLUCENT Healthcare providers drive $2.5 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 Sourcing variance is one of the most line-item-auditable opportunities in a health system and one of the easiest to misjudge, because a high-cost item is not overspend if it earns more than it costs. As our subject matter expert for this domain, you will bring that judgment into the product itself, shaping how our agents reason about contract pricing, tier compliance, and 340B integrity, while holding model output to the standard a working pharmacy or supply chain leader would apply. This position reports to Adam Albrecht, Head of Domain Intelligence. WHAT YOU'LL DO To facilitate the development of these systems, you will: • Develop and deliver subject matter expertise in pharmacy economics and healthcare supply chain to support AI product development and customer margin realization • Work closely with our engineering, product, and design teams to define and develop AI systems for pharmacy and supply chain workflows • Build proprietary benchmarks and datasets to evaluate models and AI agents against real-world sourcing and pharmacy tasks including, but not limited to: distributor and contract price audit, GPO tier compliance, 340B capture and integrity review, item master normalization, and cost-to-reimbursement analysis on high-cost items • Partner with customer delivery to understand our customer’s purchasing and value analysis cycles, identify pain points, and translate complex financial and clinical requirements into technical solutions WHAT YOU HAVE • 7+ years in hospital pharmacy business operations, supply chain, value analysis, or an equivalent function, ideally with exposure to contract pricing, purchasing compliance, and spend management • Strong proficiency with ERP and materials systems (GHX, Premier, PeopleSoft and similar), item master structure and hygiene, GPO tier mechanics, and 340B split-billing platforms • Ability to convert workflows and hypotheses into structured data, rules, and logic for algorithms and quality measurement as well as the expertise to link data points that may not already speak to each other in ways that enhance performance • Demonstrated ability to deliver high-quality analyses on demanding deadlines • Ability to effectively communicate with a variety of internal and external stakeholders, including clinicians in value analysis settings, and translate complex problems between supply chain, product, and engineering teams • Ability to define positive outcomes in situations with underspecified success criteria • Deep intellectual curiosity and eagerness to learn across domains, particularly at the intersection of healthcare sourcing and AI • Willingness and desire to do work in the trenches — e.g., grading model-flagged invoice lines against tier pricing, normalizing an item master by hand to make a category comparable, evaluating whether a flagged high-cost item is actually overspend or a well-reimbursed one. Getting AI to find price variance requires a lot of finding price variance NICE TO HAVE • Experience at a high-growth startup, or with physician preference items and service-line sourcing (ortho, cardiac, spine) • Familiarity with SQL, Python, or other data tools • Prior exposure to AI/ML concepts or prompt engineering Anticipated compensation: $175,000 – $250,000 and Equity