Applied AI Researcher

Midstream Health

About The Position

Midstream is hiring Applied Researchers to develop AI agents and models that identify financial opportunities in complex health system contracts, spend, and operational data. The role focuses on turning manual analyses into intelligent, scalable workflows that help health systems recover financial value. Researchers work closely with Engineering, Product, Value Engineers, and subject matter experts, experiment with new approaches, develop capabilities, and measure the financial impact of their work. The position involves developing and improving agents that find and validate opportunities across healthcare supply chain, pharmacy, and managed care; analyzing large, messy datasets; and building models for challenges such as pricing discrepancies, contract optimization, underpayments, and negotiation opportunities. It also includes translating expert workflows into AI-powered capabilities, advancing information extraction and agentic workflows, establishing rigorous evaluations and metrics, and helping shape Midstream’s AI-native platform.

Requirements

2–8 years of experience in data science, machine learning engineering, AI engineering, or a related field; demonstrated ability is valued alongside years of experience.
Proficiency in Python and a solid foundation in statistics, experimental design, and data modeling.
Ability to investigate unfamiliar datasets, identify meaningful patterns, and form well-reasoned hypotheses.
Experience building, debugging, and improving LLM-powered agents or workflows.
Understanding of how to design effective evaluations, identify failure modes, and systematically improve performance without unnecessary complexity.
Analytical curiosity and sound technical judgment, including the ability to understand underlying data, models, and problems when using AI tools.
Ability to connect technical improvements to measurable business results.
Initiative and ownership in fast-moving environments, including navigating ambiguity and moving problems toward resolution.
Strong collaboration and communication across technical and non-technical teams; openness to expertise and feedback, and accountability for mistakes.
Curiosity about complex domains and emerging technology, and interest in applying AI to help health systems identify and recover financial value.

Responsibilities

Develop and continuously improve AI agents that identify and validate financial opportunities in healthcare supply chain, pharmacy, and managed care.
Experiment with approaches to improve agent performance and measure success by the value the agents uncover.
Investigate large, complex healthcare datasets to identify patterns, anomalies, and relationships that reveal financial opportunities.
Develop models and analytical approaches for pricing discrepancies, contract optimization, underpayments, and negotiation opportunities.
Work with Value Engineers to translate complex manual analyses into reliable AI-powered capabilities.
Reduce manual effort while improving the speed, accuracy, and scale of opportunity identification and validation.
Develop approaches to information extraction and agentic workflows, including frameworks for building and deploying extractors across complex healthcare documents.
Collaborate with Engineering to turn successful research into scalable product capabilities.
Define evaluation frameworks and performance metrics, and test, debug, and improve models and agents.
Ensure technical performance gains translate into measurable financial value for customers.
Partner with Engineering, Product, and domain experts to improve healthcare data models, identify automation opportunities, and shape the platform.