Manager, Healthcare Analytics

twinhealth; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Twin Health in New York is seeking a Manager, Healthcare Analytics to lead high-stakes claims analyses and translate findings into actionable insights for executives, partners, and clinical stakeholders.

You will own analyses end-to-end, from raw data extraction through methodology and reporting, build reusable frameworks, and mentor a team of analysts while integrating AI‑assisted workflows. This is a visible, cross-functional role with a strong focus on impact and rigor.

Qualifications

• Background: 5+ years of experience in healthcare analytics, health economics, biostatistics, or a related applied research role, including people management or project leadership.
• Causal Inference Experti

Responsibilities

• Lead rigorous claims analyses of medical and pharmacy data to evaluate program impact, cost trends, and clinical outcomes, applying causal inference methods suited to observational data, including difference-in-differences, propensity score matching and weighting, instrumental variables, and regression discontinuity.
• Stress-test every finding with sensitivity and robustness checks, including placebo tests, pre-trend analysis, negative controls, and specification-curve analyses, so you know the defensible range of a result before it is shared externally.
• Tailor results to the audience, from board-level summaries for executives to detailed methodology appendices for sophisticated partners and plain-language explanations for non-technical stakeholders.
• Partner with client-facing teams to scope analyses, set clear expectations about what the data can and can't support, and translate findings into practical implications for operations and program design.
• Defend insights and evaluation methodology under scrutiny from partner analytics teams, benefits consultants, and third-party auditors.
• Align internal stakeholders across sales, client success, and data teams, agreeing on what an analysis can support before it is promised externally and keeping methodology and data decisions consistent across teams.
• Contribute to the evidence base through peer-reviewed publications and conference presentations, bringing academic rigor to applied, commercial analyses.
• Build reusable analytical frameworks so that recurring analyses, such as total cost of care studies, adherence analyses, and outcomes evaluations, can be reproduced and audited.
• Make AI a core part of the workflow by using tools such as Claude and Claude Code to draft and review analysis code, accelerate data cleaning and QA, and speed up documentation and reporting. You'll coach analysts to do the same and help set team norms for where AI speeds work up and where it needs a human check.

Skills

Causal inference

Healthcare analytics

Leadership

Tools

Claude

Claude Code

Job description

Twin Health

At Twin Health, we empower people to improve and prevent chronic metabolic diseases, like type 2 diabetes and obesity, with a new standard of care. Twin Health is the only company applying AI Digital Twin technology exclusively toward metabolic health.

We start by building a dynamic model of each person's metabolism - drawing on thousands of data points from CGMs, smartwatches, and meal logs - that maps their personal path to better health.

Guided by a dedicated clinical care team, our members have lowered their A1C below the diabetes range, achieved lasting weight loss, and reduced or even eliminated medications, all while living healthier, happier lives.

Working here

Our team at Twin Health is passionate, talented, and united by a shared purpose: to improve the metabolic health and happiness of our members. We believe in empowering every Twin to make a meaningful impact for our members, our clients, and each other, while enjoying a supportive, collaborative work environment.

Twin has been recognized not only for our innovation but also for our culture, including: Innovator of the Year by the Employer Health Innovation Roundtable (EHIR), selected to CB Insights' Digital Health 150, and named one of Newsweek's Top Most Loved Workplace® .

With more than $100 million raised in recent funding, including a $53 million Series E round in 2025 led by Maj Invest, and a $50 million investment in 2023 led by Temasek, Twin is scaling rapidly across the U.S. and globally. Backed by leading venture firms like ICONIQ Growth, Sequoia, Sofina, Temasek, and Peak XV, we are building the most impactful digital health company in the world.

Join us as we reinvent the standard of care in metabolic health.

Opportunity

This role is a unique opportunity to lead the insights that show what Twin's program delivers. You won't just run models; you'll own rigorous, high-stakes claims analyses and turn them into findings that executives, partners, and clinical stakeholders can act on.

As Manager, Healthcare Analytics, you'll work at the intersection of causal inference, messy real-world claims data, and client-facing communication. You'll own analyses from end to end, from raw claims extraction through methodology to a polished, decision-ready narrative. You'll also lead and develop a team of analysts. Your focus is insights: program evaluation, cost and outcome trends, and evidence that informs partners and Twin's own decisions. Performance guarantee design, measurement, and settlement are owned by Twin's actuarial team, and you'll partner closely with them so that insights and guarantee results tell a consistent story. This is a highly visible role, working closely with sales, client success, actuarial, and data teams.

Responsibilities

• Lead rigorous claims analyses of medical and pharmacy data to evaluate program impact, cost trends, and clinical outcomes, applying causal inference methods suited to observational data, including difference-in-differences, propensity score matching and weighting, instrumental variables, and regression discontinuity.
• Stress-test every finding with sensitivity and robustness checks, including placebo tests, pre-trend analysis, negative controls, and specification-curve analyses, so you know the defensible range of a result before it is shared externally.
• Tailor results to the audience, from board-level summaries for executives to detailed methodology appendices for sophisticated partners and plain-language explanations for non-technical stakeholders.
• Partner with client-facing teams to scope analyses, set clear expectations about what the data can and can't support, and translate findings into practical implications for operations and program design.
• Defend insights and evaluation methodology under scrutiny from partner analytics teams, benefits consultants, and third-party auditors.
• Align internal stakeholders across sales, client success, and data teams, agreeing on what an analysis can support before it is promised externally and keeping methodology and data decisions consistent across teams.
• Contribute to the evidence base through peer-reviewed publications and conference presentations, bringing academic rigor to applied, commercial analyses.
• Build reusable analytical frameworks so that recurring analyses, such as total cost of care studies, adherence analyses, and outcomes evaluations, can be reproduced and audited.
• Make AI a core part of the workflow by using tools such as Claude and Claude Code to draft and review analysis code, accelerate data cleaning and QA, and speed up documentation and reporting. You'll coach analysts to do the same and help set team norms for where AI speeds work up and where it needs a human check.

Qualifications

Background: 5+ years of experience in healthcare analytics, health economics, biostatistics, or a related applied research role, including people management or project leadership.

Causal Inference Experti