ABOUT THE ROLE
At Ensemble HP, we harness AI to revolutionize RCM processes. We aim to ensure every patient's journey informs healthcare decisions, optimizes treatment plans, and promotes drug discoveries. We aspire to deliver timely and precise care through comprehensive analysis of patient health records. If you share our passion for healthcare advancement through technology, let's reshape the future together.
As a Clinical Informatician, your clinical perspective will be essential in guiding the design and validation of AI-driven solutions for revenue cycle management (RCM) and clinical guideline–based workflows. You will work in a hybrid capacity, with a balance of remote work and in-office presence. Your role is strategically impactful, requiring you to be physically present in the office on designated days to collaborate closely with cross-functional teams. The flexibility of remote work will allow you to join late meetings/discussions that can be effectively attended outside the office while ensuring your in-office time maximizes your communication with your team and the team in the US office.
CORE RESPONSIBILITIES
RCM Knowledge Architecture & Model Design
Design and implement scalable AI frameworks specifically for RCM automation.
Translate complex clinical and financial logic into knowledge representations to ensure the AI accurately predicts "next-best-action" in RCM pipeline and enable the AI to adapt to different regional and contractual requirements.
Classify and review RCM logic suggestions from cross-functional teams to continuously expand the RCM knowledge base.
Develop an ontology for RCM specific workstreams to facilitate the process automation
Process and AI Optimization
Contribute to the continuous improvement of AI outputs, particularly in the analysis of RCM knowledge and next steps action prediction, ensuring high-quality and reliable results.
Identify inefficiencies in the RCM automation pipeline and propose architectural improvements to enhance data throughput and accuracy.
Design agentic AI frameworks capable of real-time reasoning to resolve complex processees and automate next-best-action workflows.
AI Output Validation
Validate each release component (ontology, Symbolic resources etc.) identifying and solving inefficiencies in current processes and propose process improvements.
Perform rigorous validation of AI-generated outputs, specifically focusing on the analysis of RCM knowledge and the ability of the AI to understand the process and predict next action steps.
Establish quality benchmarks for LLM performance, ensuring high precision in the automation of clinical appeals and prior authorizations.
Cross-Functional Collaboration
Communicate complex informatics methodologies to both technical AI teams and non-technical RCM stakeholders (e.g., Revenue Cycle directors, Clinical Appeals nurses).
Collaborate with AI engineers and RCM subject matter experts to develop a roadmap for knowledge-driven automation, ensuring the RCM framework supports both current product needs and future innovations in healthcare AI.
Partner with AI engineers to integrate Large Language Models (LLMs) with structured ontologies (Hybrid AI), ensuring model outputs are grounded in "source of truth" clinical standards and RCM rules.
Documentation and Communication
Document and present findings, methodologies, and best practices to both technical and non-technical audiences. Share in the creation of cross-functional tasks’ guidelines and rules.
Tooling & Platform Management
Manage and utilize AI tools and platforms to streamline the lifecycle of data models.
Provide feedback for the optimization of internal informatics tools to increase the speed of production deployment
Continuous Learning and Innovation
Stay current with advancements in AI, knowledge engineering, and their applications in healthcare and RCM.
BASIC Q
UALIFICATIONS
A bachelor's degree in Medicine, Pharmacy, Biotechnology, or related field.
Proficient use of Microsoft Suite applications.
Specialized clinical and scientific expertise relevant to clinical data, such as prior experience with real-world datasets, designing clinical algorithms or creating other complex logic using clinical data.
Familiarity with healthcare data and interoperability with standard terminologies. (e.g., HL7, FHIR, ICD-10, SNOMED CT, RxNorm).
Familiarity with RCM concepts such as “Front End”, “Accounts Receivable” and “Coordination of Benefits”
Strong understanding of disease processes, diagnostics, therapeutics, and clinical workflows, with the ability to translate this knowledge into structured concepts.
Strong skills in analyzing, researching, and synthesizing large amounts of data.
Strong organizational and time management skills, with the capacity to adapt to change.
Understanding and familiarity with the basics of AI, such as, but not limited to, Machine learning, Symbolic AI, LLMs, and Formal Logic.
PREFERRED QUALIFICATIONS
Knowledge in the field of insurance
Knowledge of programming or scripting languages (e.g., Python, SQL, R) is nice to have.
Prior experience with ontology development, ontology enrichment, or clinical knowledge representation.
Hands-on experience with data cleaning, manipulation, or validation in healthcare contexts.
Ability to design, conduct, and interpret analyses to support clinical decision-making and healthcare outcomes.
Clinical research experience, particularly involving structured data capture or analysis.
Familiarity with the basic principles, practices, and policies related to biomedical research and protection of human subjects.
A postgraduate degree or equivalent research experience in informatics, bioinformatics, or a related field is desirable.