• Responsible for the preparation and submission of claims for accounts to ensure timely reimbursements. • Communicate with nursing facility staff, physician offices, and insurance companies to maintain payment deliverables for online claim submissions. • Follows established procedures to execute routine business support tasks under general supervision. • Develops effective relationships with all team members. • Conducts review and research of rejected claims and takes action for resolution. • Handles work backlog of denied claims for timely resubmission. • Ensures compliance with all government and regulatory requirements.

• Supports comprehensive coordination of medical services including intake and outgoing calls. • Reviews eligibility and benefits, opens pre-certification cases, and approves or sends to nursing staff for review. • Evaluates patients using targeted intervention business rules and processes to identify needed medical services. • Communicates health care service delivery based on outcomes noted by the nurse or medical director. • Performs non-medical research pertinent to the establishment, maintenance, and closure of open cases. • Provides support services to team members by answering telephone calls, taking accurate messages, and supporting electronic transmission review.

• Serve as a subject matter expert on power systems within your project teams, ensuring technical rigor and feasibility of proposed solutions. • Independently scope and execute multiple analytical workstreams in parallel, especially those related to markets and grids-focused projects, and support team members in scoping and executing analyses. • Locate, synthesize, and analyze data that allows RMI to shed new light on problems and devise creative solutions. • Use your research and analysis to develop hypotheses, insights, and recommendations that accelerate clean energy deployment, drawing on various change levers such as deployment of technical solutions, capacity building, mobilization of capital, or power sector planning. • Advise on and/or help implement RMI's use of key modeling and analytical tools and resources (e.g., power flow models, production cost models, resource adequacy models, accreditation methods, etc.) and apply this to: • Use, improve, and quality-control both your and teammates existing models. • Develop systems to share and organize technical work across project teams. • Mentor staff to develop and use these tools / skill sets. • Research novel tools and analytical options that RMI could leverage in future project work, including software innovations such as automation, AI, etc. • With support from senior staff, structure and create presentations and writing that bring new insights to partners in a clear and compelling manner. • Contribute publicly at conferences, share expertise in response to media requests, and establish and maintain relationships with a network of technical experts that RMI may collaborate with. • Travel up to 20%, including internationally.

• Update training and test model databases with new or amended synthetic textual and image data. • Modify and refine machine learning data creation, annotation, and rating guidelines. • Initiate model training processes using internal tools and command-line interfaces. • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment. • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees. • Handle data efficiently, ensuring its integrity throughout the workflow. • Engage in data relevance tasks, ensuring data sets are aligned with project goals. • Annotate data accurately, ensuring it adheres to set guidelines. • Conduct manual quality analysis of model results. • Recognize error patterns and report anomalies for further investigation. • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team. • Implement basic quality control measures and ensure the reliability of processed data. • Utilize intermediate data analysis techniques to extract insights and inform decision-making. • Arbitrate discrepancies effectively, ensuring consistent data quality. • Apply basic knowledge of natural language processing and linguistics to data processing tasks. • Ensure linguistic accuracy in all processed and annotated data.