Principal Quantitative Researcher, Federal Health Program Implementation and Evaluation

Commence; Washington (District of Columbia); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Commence seeks a Principal Quantitative Researcher to lead CMS/CMMI APM design, implementation and evaluation using Medicare/Medicaid data. You will translate policy goals into methodologies and collaborate with economists, data scientists and engineers to apply advanced analytics on the Commence platform.

The role requires hands-on CMS/CMMI experience, strong federal-writing ability, and the capacity to mentor junior researchers while delivering high-quality reports on time and within budget.

Qualifications

• Ph.D. in economics/health policy or a related field with 9+ years of experience or a Master’s with 13+ years.
• Hands-on CMS/CMMI alternative payment models implementation and/or evaluation experience.
• Strong writing for federal audiences and proposal-writing experience.

Responsibilities

• Lead the translation of model design documents into operational methodologies using CMS/CMMI data.
• Design and implement value-based care methodologies and evaluation plans.
• Lead evaluations with quasi-experimental designs and appropriate comparison groups.
• Collaborate with economists, data scientists, and engineers to apply ML-based methods.
• Prepare methodology documents, evaluation reports, and client briefings.
• Contribute to proposal design and mentor junior researchers and analysts.
• Manage projects, set priorities, and ensure timely, high-quality deliverables.

Skills

Analytics

Education

Ph.D. in economics/health policy or related field

Master's degree

Tools

Databricks

Power BI

Tableau

SAS

R

Python

SQL

Job description

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.

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 Principal Quantitative Researcher, Alternative Payment Model Implementation and Evaluation plays a pivotal role in the implementation and operation of healthcare programs and initiatives, the generation of actionable insights that inform decision‑making for federal agencies such as the CMS Innovation Center (CMMI), and Commence’s growth in federal health research.

This position leads the design and execution of implementation, operations and evaluation tasks for CMS/CMMI alternative payment models (APMs).

Working closely with Commence’s data science and technology teams, the researcher helps bring advanced analytics to model implementation and evaluation by leveraging the capabilities of the Commence platform, driving greater efficiency and deeper insights.

The ideal candidate combines hands‑on implementation and/or evaluation experience on CMS/CMMI APMs with strong analytical, managerial, client‑engagement and storytelling skills, a strategic mindset, and a passion for driving measurable improvements in health care quality and value.

• Lead the translation of model design documents and policy goals into operational methodologies and specifications using Medicare and Medicaid claims, enrollment, and programmatic data, as well as other data sources including surveys and census data.
• Implementation: Lead the development, refinement, and implementation of value‑based care methodologies, including participant screening and monitoring; beneficiary attribution; payment mechanisms, benchmarking and financial adjustments include risk adjustment; selection, adaptation, and scoring of quality measures.
• Evaluation: Lead the design and execution of evaluations, including monitoring methodologies, comparison groups (e.g., propensity score matching, synthetic controls) and quasi‑experimental designs (e.g., difference-in-differences, event studies) to estimate impact on healthcare spending, utilization, and quality.
• Partner with economists, data scientists, and engineers to conduct research, create prototypes, and apply ML‑based methods on the Commence platform to develop novel approaches to conduct implementation and evaluation work.
• Lead the write up of methodology documents, evaluation reports, and briefings for CMMI model teams, turning findings into clear, actionable recommendations.
• Lead the design and write up of technical approaches for CMS/CMMI and other federal agency proposals and serve in key project roles; mentor junior researchers and analysts.
• Effectively 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 9+ years of relevant experience; or a Master’s degree with 13+ years.
• Hands‑on experience implementing and/or evaluating CMS/CMMI alternative payment models; experience with both is preferred.
• Working knowledge of at least two of: participant screening and monitoring, beneficiary attribution, payments and financial incentive design, quality measurement, comparison group design, quasi‑experimental evaluation methods (difference in difference, event study); mixed‑methods.
• 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.
• Experience leading main tasks or projects and managing and mentoring staff.
• 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.

Commence 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 [phone] or [e-mail]. Please note that unless you are requesting an accommodation, all applications must be submitted through our online application system.