Staff Data Scientist, Healthcare Economics
Pomelo Care is hiring a Staff Data Scientist, Healthcare Economics for a remote role open to applicants in United States. It pays $220k-$250k a year and Level rates it ; you can apply on Pomelo Care.
Level's read on this job
- Level rates this data scientist role Little AI ●○○○: aI is not part of the work.
- The listed pay starts 33% above the typical data scientist posting on Level.
- The posting lists this role as remote.
- Tools and skills the posting cites include health economics, statistical analysis and program evaluation.
- Level lists 81 other open roles at Pomelo Care.
AI in this role
Own and execute health economics analyses and outcome evaluations for virtual medical practice programs.
Pomelo Care is the leading virtual medical practice for women and children, providing care across pregnancy, postpartum, pediatrics, menopause, and perimenopause. We combine proactive, 24/7 clinical care with technology that helps us reach patients earlier, identify risks sooner, and deliver personalized care throughout their journey. Our team includes clinicians, technologists, operators, and problem-solvers working together to make high-quality care more accessible for families nationwide.
About The Role
Your north star: Own how Pomelo's clinical and economic impact is measured, proven, and presented - to our payer partners, to external partners, and in published research. We're looking for a data scientist experienced in healthcare outcomes assessment or program evaluation to join our Health Economics team. Trustworthy, actionable data plays a critical role in Pomelo's mission to improve pregnancy outcomes.
This role goes far beyond reporting. The analyses you produce feed directly into renewal and expansion negotiations with national payers, shape how new risk-based and value-based offerings are structured, and become the evidence base we publish. You'll inherit a strong foundation of established methods and infrastructure, and you'll regularly need to build on it to answer novel questions, explore new methodologies, and communicate results to audiences with very different backgrounds. You will have direct influence on how we measure impact and tell our story externally.
What you'll do
Own the question as well as the analysis. Take large, ambiguous mandates and break them into definitions, assumptions, and key questions to align stakeholders
Architect and execute analyses that assess the outcomes of Pomelo Care's programs in a scalable, repeatable way. Where existing approaches don't reach, you'll extend them or build something new, and stand behind those choices under scrutiny
Lead Pomelo's technical engagement with external partners: presenting directly, aligning on methodology and parameters, and building credibility with evaluation teams
Drive our evidence strategy end to end: partner-facing reporting, conference presentations, and peer-reviewed publications
Build data tables, pipelines, and dashboards that combine diverse health data sources and make insights accessible across teams
Identify opportunities to scale and automate insights in partnership with the data and analytics engineering teams
Serve as Pomelo's expert on statistics and health economics: define the methodologies we use for evaluation, mentor other data scientists, and guide where we invest technically
Who you are
A collaborative problem solver and analytic thinker who is focused on driving impact, and excited to work at a startup.
6+ years professional experience developing statistical models to answer complex healthcare problems using varied techniques (e.g., propensity score matching, linear and logistic regressions, k-means clustering, difference-in-differences, decision trees)
Experience with cost of care or clinical outcomes target setting at a payer, managed care organization, integrated delivery network, value-based care provider, or healthcare consulting firm
Experience presenting statistical analyses to external stakeholders with varied technical expertise
Proficient in Python or R and SQL
You do your best work when the goal is ambiguous. You are comfortable telling others "here's what I recommend and why" rather than waiting to be told what to analyze
You have the technical depth to run a publication-grade evaluation and the judgment to know when a scrappy proof-of-concept is the better call. You never lose sight of why the work matters to the business
Excellent written and verbal communicator, comfortable across technical and non-technical audiences
Formal training in statistics, econometrics, or actuarial science
Experience with risk-based or value-based contracting, including opportunity sizing and ROI modeling
Experience with medical claims data
Peer-reviewed publications in health outcomes or health economics
Experience with data dashboarding or visualization (e.g., Looker, Tableau, Metabase)
Experience working with dbt
Compensation:
The expected base salary range offered for this role is $220,000 - $250,000. This role is also eligible for equity, giving you an ownership stake in Pomelo’s mission. Actual compensation may vary based on relevant experience, skills, competencies, and certifications.
Why you should join our team
By joining Pomelo, you will get in on the ground floor of a fast-moving, well-funded, and mission-driven startup that always puts the patient first. You will learn, grow and be challenged, and have fun with your team while doing it.
We strive to create an environment where employees from all backgrounds are respected. We value working across disciplines, moving fast, data-driven decision making, learning, and always putting the patient first.
Benefits and Perks:
Comprehensive Health, Dental, and Vision coverage for employees and their families
High deductible Health Plans with Health Savings Account (HSA) options
Flexible Spending Account (FSA)
Equity grant participation
401(k) program
Competitive vacation policy
16 weeks paid parental leave
Fully remote work flexibility (within the US)
We are committed to hiring the best team to improve outcomes for all mothers and babies. To solve the complex challenges facing the diverse population we serve, we need diverse perspectives, actively welcoming people of all races, ages, sexual orientations, gender identities and expressions, national origins, religions, disabilities, and veteran statuses. We strive to cultivate an inclusive and respectful environment where team members thrive by working across disciplines, moving fast, making data driven decisions, learning continuously, and always putting the patient first.
How we rate this
Staff Data Scientist, Healthcare Economics at Pomelo Care rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $220k
- Typical data scientist job
- $166k
This posting starts 33% above the typical data scientist job. See data scientist jobs
Questions you could be asked
- Tell me about a project where health economics was part of your work. What did you do?
- Tell me about a project where statistical analysis was part of your work. What did you do?
- Tell me about a project where program evaluation was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where healthcare outcomes was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Health Economics, Statistical Analysis, Program Evaluation, Data Science, and Healthcare Outcomes. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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