About Us: Our purpose is to help clients exceed their financial health goals. Across the reimbursement cycle, our scalable solutions and clinical expertise help solve programmatic needs. Enabling our teams with leading technology allows analytics to guide our solutions and keeps us accountable achieving goals. We build long-term careers by investing in YOU. We seek to create an environment that cultivates your professional development and personal growth, as we believe your success is our success. JOB SUMMARY: Domain: Healthcare Payer / Revenue Cycle Management | Programs: Medicare Advantage, ACA (Commercial Exchange), Medicaid | Platform: AWS | Role Type: Individual Contributor (hands‑on) We are seeking a hands‑on Senior Data Scientist with strong medical coding and clinical domain expertise to support risk adjustment and quality initiatives for Value‑Based Care programs across Medicare Advantage, ACA health plans, and Medicaid. This role focuses primarily on Risk Adjustment (HCC/RAF) and clinical indications, leveraging claims and clinical notes to deliver accurate, explainable, complete, and compliant analytics. The position is well‑suited for candidates with backgrounds in data science, biostatistics, bioinformatics, or clinical informatics, and experience applying traditional NLP and modern AI (LLMs, GenAI, agentic workflows) in regulated healthcare environments. ESSENTIAL DUTIES AND RESPONSIBILITIES: Note: The essential duties and responsibilities below are intended to describe the general duties and responsibilities of this position and are not intended to be an exhaustive statement of duties. This position may perform all or most of the primary duties listed below. Specific tasks, responsibilities or competencies may be documented in the Team Member’s performance objectives as outlined by the Team Member’s immediate Leadership Team Member. Location: Remote within US only We are seeking a hands‑on Senior Data Scientist with strong medical coding and clinical domain expertise to support risk adjustment and quality initiatives for Value‑Based Care programs across Medicare Advantage, ACA health plans, and Medicaid. This role focuses primarily on Risk Adjustment (HCC/RAF) and clinical indications, leveraging claims and clinical notes to deliver accurate, explainable, complete, and compliant analytics. The position is well‑suited for candidates with backgrounds in data science, biostatistics, bioinformatics, or clinical informatics, and experience applying traditional NLP and modern AI (LLMs, GenAI, agentic workflows) in regulated healthcare environments. - Build and maintain risk‑adjustment analytic modeling (HCC suspecting, recapture models, RAF forecasting). - Apply NLP and GenAI to medical records and clinical notes to extract structured clinical evidence. - Develop LLM‑assisted and agentic workflows to support medical record coding review, evidence summarization, and improved productivity and accuracy. - Perform forecasting and scenario analysis tied to operational capacity and financial impact. - Monitor model performance, bias, drift, and documentation sufficiency. - Ensure analytics are explainable, auditable, and compliant. - Partner closely with Product, Engineering, Coding, Clinical, Compliance, and Operations teams. - Translate analytics into actionable signals embedded in payer workflows. - (Exposure to quality/HEDIS is a plus but not a primary focus.) - (Exposure to/knowledge of physician workflows and patient condition capture/documentation is a plus.) Required Skills & Experience - Strong foundation in statistics, applied machine learning, and data analysis. - Advanced Python and SQL. - Experience working with medical records, claims and clinical data. - Deep understanding of Risk Adjustment (CMS‑HCC, RAF mechanics). - Deep understanding of medical coding (ICD‑10, CPT, DRG, NDC) and clinical documentation workflows. - Experience delivering explainable models in regulated or audit‑sensitive environments. - Clinical background and cross-referencing to medical record documentation requirements. - Knowledge of CDI (Clinical Documentation Integrity) policies and procedures - Strong communication and cross‑functional collaboration skills. Technical & AI Stack - Languages: Python and SQL are required, R is a plus. - ML/DS model-building: pandas, numpy, scikit‑learn. - NLP/GenAI: Large Language Models (LLMs), prompt engineering, retrieval‑augmented generation (RAG) pipelines, agentic AI for task orchestration and review; clinical NLP frameworks such as scispaCy and BioBERT. - Data & Compute: AWS (RDS for SQL Server, S3, Redshift, Snowflake, Athena), Azure (Foundry, OpenAI Service, Machine Learning). - Analytics: Jupyter, Power BI. - MLOps: experiment tracking and model/version management (e.g., MLflow). Preferred Background - Experience supporting Medicare Advantage risk adjustment programs. - Experience with ACA health plan populations and Medicaid. - Background in bioinformatics, biostatistics, public health, biomedical informatics, or clinical data science. - Experience with medical record coding and CDI. - Familiarity with FHIR data and healthcare interoperability standards. - Prior work in payer RCM or value‑based care analytics. - Experience supporting compliance‑reviewed or audit‑exposed models. - Practical experience deploying or piloting LLM‑ or GenAI‑based solutions. PHYSICAL DEMANDS: Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions as described. Regular eye-hand coordination and manual dexterity is required to operate office equipment. The ability to perform work at a computer terminal for 6-8 hours a day and function in an environment with constant interruptions is required. At times, Team Members are subject to sitting for prolonged periods. Infrequently, Team Member must be able to lift and move material weighing up to 20 lbs. Team Member may experience elevated levels of stress during periods of increased activity and with work entailing multiple deadlines. A job description is only intended as a guideline and is only part of the Team Member’s function. The company has reviewed this job description to ensure that the essential functions and basic duties have been included. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate.

• Enhancing Models: Continuously improving existing models by incorporating new features, fine-tuning parameters, and utilizing additional data. • Algorithm Development: Collaborating with our Machine Learning Engineering team to develop and deploy scalable supervised and unsupervised learning algorithms. • Data Exploration: Identifying and exploring new data sources while researching innovative ways to leverage both new and existing data effectively. • Solution Research: Investigating new Machine Learning solutions to optimize every step of our value chain. • A/B Testing: Regularly conducting and evaluating A/B tests to drive insights and refine our strategies.

• Design and deploy AI agent workflows to automate recurring analytical tasks, data summarization, and insight generation pipelines. • Evaluate and integrate LLM-based tools into the data team's workflow, assessing their reliability, accuracy, and fitness for analytical use cases. • Collaborate with product and business teams to define analytical questions, success metrics, and KPIs. • Build and maintain analytics foundation using SQL and dbt, enabling reliable reporting and self-serve analytics. • Design, build, and maintain Tableau dashboards that bring metrics to life and support day-to-day decision-making. • Perform A/B testing and experimentation, including experiment design, statistical inference, significance testing, and result interpretation. • Perform ad-hoc, exploratory, and statistical analyses to uncover insights and validate hypotheses. • Communicate findings clearly to both technical and non-technical stakeholders, translating data into actionable recommendations. • Partner with stakeholders to iterate on metrics, dashboards, and analyses as business needs evolve.

• Support meeting planners in managing attendee registration for conferences and events • Ensure the smooth execution of data-related tasks • Maintain accurate attendee data • Collaborate with event stakeholders • Provide database management to ensure consistency and accuracy • Assist in the development, testing, and management of event communications and online registration • Support attendees throughout the registration process • Manage room blocks, activity scheduling and onsite execution support including post-event attendee reporting • Domestic and/or international travel may be required with this role.