SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 175,000 - 250,000 / annual
Translucent is an AI-native financial platform built exclusively for healthcare providers. The company was founded in 2024 and is backed by GV, NEA, FPV, and Virtue. Healthcare providers operate on razor-thin 2–5% margins while managing $2.5 trillion in annual medical expenditures, yet their finance teams spend excessive time on manual data work rather than strategic decision-making. Translucent deploys AI agents that run 24/7 to automate financial workflows and reasoning.
As Subject Matter Expert for Workforce & Labor Productivity, you will be the domain authority shaping how the platform's AI agents reason about healthcare labor—the largest line item on most provider income statements. Labor variance analysis is complex: staffing issues can stem from modeling problems, demand fluctuations, or competitive pressures. Your role bridges operations and AI product development.
Key responsibilities include:
- Develop and deliver subject matter expertise in healthcare workforce and productivity management to support AI product development and customer outcomes
- Collaborate with engineering, product, and design teams to define and build AI systems for workforce and labor workflows
- Build proprietary benchmarks and datasets to evaluate AI models and agents against real-world tasks: agency/premium labor analysis, staffing-to-census matching, productivity benchmarking, overtime attribution, and schedule variance review
- Partner with customer delivery teams to understand staffing/scheduling cycles, identify pain points, and translate operational requirements into technical solutions
Required qualifications:
- 7+ years in healthcare workforce operations, nursing operations, staffing management, or equivalent
- Strong proficiency with time-and-attendance systems (UKG/Kronos, API Healthcare) and labor benchmarks (Premier, Vizient)
- Fluency in productive vs. non-productive hours and worked-hours-per-unit-of-service definitions
- Ability to convert workflows and hypotheses into structured data, rules, and logic for algorithms
- Demonstrated ability to deliver high-quality analyses on tight deadlines
- Strong communication skills across workforce operations, product, and engineering teams
- Ability to define success criteria in ambiguous situations
- Deep curiosity about workforce management and AI intersection
- Willingness to do detailed analytical work: grading model outputs, reconstructing schedules, validating decisions against census data
Nice-to-have: startup experience, exposure to multiple labor markets/union environments, SQL/Python proficiency, familiarity with AI/ML or prompt engineering.
