Applied AI Researcher

Own the development and continuous improvement of agents that identify and validate financial opportunities across healthcare supply chain, pharmacy, and managed care. Experiment with new approaches, systematically improve performance, and measure success by the value your agents uncover.

Investigate large, messy healthcare datasets to uncover patterns, anomalies, and relationships that reveal financial opportunities. Develop models and analytical approaches to problems such as pricing discrepancies, contract optimization, underpayments, and negotiation opportunities.

Work closely with our Value Engineers to understand the complex analyses they perform today and translate those workflows into reliable, AI-powered capabilities. Help reduce manual effort while improving the speed, accuracy, and scale of opportunity identification and validation.

Develop novel approaches to information extraction and agentic workflows, including frameworks that make it faster to build and deploy new extractors across complex healthcare documents. Collaborate with Engineering to translate successful research into scalable product capabilities.

Define clear evaluation frameworks and performance metrics from the start. Continuously test, debug, and improve models and agents, ensuring that gains in technical performance translate into measurable financial value for our customers.

Partner with Engineering, Product, and domain experts to improve how we model healthcare data, identify new opportunities for automation, and influence the evolution of our AI-native platform. Bring curiosity, strong technical judgment, and a willingness to learn from the people closest to the problems we're solving.

• Experienced in applied AI and machine learning: You have 2–8 years of experience in data science, machine learning engineering, AI engineering, or related fields. We're hiring across multiple levels and value demonstrated ability over years of experience alone.

• Strong in data analysis and experimentation: You're proficient in Python, with a solid foundation in statistics, experimental design, and data modeling. You can quickly investigate unfamiliar datasets, identify meaningful patterns, and form well-reasoned hypotheses.

• Hands-on with AI agents: You have experience building, debugging, and improving LLM-powered agents or workflows. You understand how to design effective evaluations, identify failure modes, and systematically improve performance without introducing unnecessary complexity.

• A rigorous problem-solver: You combine analytical curiosity with sound technical judgment. You use AI tools to accelerate your work but develop your own understanding of the underlying data, models, and problems you're solving.

• Outcome-oriented: You're motivated by solving real business problems and can connect technical improvements to measurable results. You care as much about the value your work creates as the sophistication of the approach.

• A high-ownership builder: You thrive in fast-moving environments, take initiative when faced with ambiguity, and know when to ask questions, involve others, or independently push a problem toward resolution.

• Collaborative and thoughtful: You actively seek expertise, communicate openly, and work well across technical and non-technical teams. You take ownership of mistakes, welcome feedback, and contribute to a culture of continuous improvement.

• Curious and mission-driven: You enjoy experimenting with new ideas, learning complex domains, and applying emerging technology to meaningful problems. You're excited by the opportunity to use AI to transform how health systems identify and recover financial value.