Senior Quantitative Researcher - Federal Health Program

Description At Commence, we’re the start of a new age of data-centric transformation, elevating health outcomes and powering better, more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers, technology that advances performance, and clinical expertise that builds trust to create a more efficient path to quality care. At Commence, we’re the start of a new age of data-centric transformation, elevating health outcomes and powering better, more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers, technology that advances performance, and clinical expertise that builds trust to create a more efficient path to quality care. With human-centered, healthcare-relevant, and value-based solutions, we create new possibilities with data. We provide proof beyond the concept and performance beyond the scope with a focus on efficiencies that transform the lives of those we serve. With a culture driven by purpose, straightforward communication and clinical domain expertise, Commence cuts straight to better care. Requirements The Senior Quantitative Researcher , Alternative Payment Model Monitoring plays a pivotal role in generating actionable insights that inform CMS Innovation Center (CMMI) decision-making and support Commence's growth in federal health research. This position plays a key role in the design and execution of monitoring for CMS/CMMI alternative payment models (APMs), from monitoring frameworks, performance metrics, and data collection plans to real-time monitoring of participant performance and compliance, dashboards, and risk reports that support federal program oversight. Working closely with Commence's data science and technology teams, the researcher helps bring advanced analytics to monitoring by leveraging the capabilities of the Commence platform, driving greater efficiency and deeper insights. The ideal candidate combines hands-on APM monitoring experience for CMS/CMMI with strong analytical and storytelling skills, a strategic mindset, and a passion for driving measurable improvements in health care quality and value. Translate model design documents and participation agreements into monitoring specifications using Medicare claims, enrollment, and participant-reported data. Design monitoring frameworks for CMMI models: logic models, measures, data sources, benchmarks, analytic methods, and reporting. Detect and investigate unintended consequences such as risk selection, coding intensity, care stinting, and shifts in referral or site-of-care patterns. Partner with data scientists and engineers to build dashboards, automated reporting, and ML-based anomaly detection and early-warning signals on the Commence platform. Write monitoring reports, briefings, and risk summaries for CMMI model teams, turning findings into clear, actionable recommendations. Design and write technical approaches for CMS/CMMI and other federal agency proposals and serve in key project roles. Apply monitoring methods to our quality measurement and performance-reporting work for CMS and state partners; mentor junior researchers and analysts. Manage teams, set priorities, coordinate tasks, engage clients and stakeholders, and ensure high-quality reports and products are delivered on time and within budget. Qualifications Ph.D. in economics, health services research, health policy, public health, or a related field with 4+ years of relevant experience; or a Master’s degree with 8+ years. Hands-on experience monitoring CMS/CMMI alternative payment models. Working knowledge of APM and value-based care mechanics: beneficiary attribution, quality scoring, capitated payments, bundled payments, financial incentives, benchmarking, risk adjustment. Experience with Medicare and/or Medicaid administrative and claims data (e.g., CCW, IDR, VRDC). Clear and concise writing for federal audiences; proposal-writing experience. Must be authorized to work in the U.S. and able to obtain and maintain a CMS-required background investigation (public trust). Preferred Skills And Competencies Experience with Databricks or other cloud analytics platforms and with Power BI, Tableau, or similar. Proficiency in SAS, R, Python, or SQL. Work Environment/Physical Demands The work environment and physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is a remote position. Occasional travel to the Baltimore/Washington, DC area for client meetings, orals, and team events. While performing the duties of this job, the employee regularly works in a climate-controlled environment. Candidates must be able to sit, read, work on a computer, and watch a computer screen for extended periods of time. Occasionally required to stand, walk, use hands and fingers, kneel or crouch. Extended hours may be needed around proposal deadlines and key deliverables. Commence' headquarters are in Virginia Beach, VA, however we are open to remote candidates in the following states: AZ, AR, CO, DE, FL, GA, IL, IN, KS, KY, MA, MD, MI, MS, MO, MT, NC, NE, NV, NY, OH, OK, PA, SC, TN, TX, VA, DC, WI, WA and WV* Commence is an equal employment opportunity employer. All personnel processes are merit-based and applied without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military and veteran status or any other characteristic protected by applicable law. CommenceI is committed to providing equal employment opportunities to all applicants, including individuals with disabilities. If you require a reasonable accommodation to participate in the application process due to a disability, please contact Human Resources at View phone number on click.appcast.io or View email address on click.appcast.io. Please note that unless you are requesting an accommodation, all applications must be submitted through our online application system. #J-18808-Ljbffr