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Business Analytics Lead - Predictive Modeling
- New York, New York, United States
- New York, New York, United States
About
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.
This role is a unique opportunity to directly influence how a leading health-tech company scales. You won't just analyze data; you'll build the tools that shape our strategy.
As a Lead Analyst, you’ll own end-to-end analytics in business critical areas like connecting clinical outcomes to LTV. You will take these projects from data extraction through modeling and communication of results to senior leadership. Additionally, you’ll work with large and complex datasets to develop novel KPIs as Twin expands its lines of business. This is an opportunity to apply technical skill and business intuition in a highly visible role, while collaborating with leaders across finance, product, and operations teams.
Responsibilities
Develop and implement Predictive Models to optimize core business operations, such as forecasting member-level revenue or predicting clinical resource demand (staffing optimization).
Focus on Prescriptive Analytics by designing solutions (e.g., optimization algorithms, simulation models) that recommend the most cost-effective and efficient actions for clinical operations and member support teams.
Define key business KPIs, establish operational dashboards, and create automated reports that provide real-time visibility into business health and efficiency.
Lead the Design and Analysis of A/B Tests and quasi-experiments focused on operational improvements (e.g., messaging frequency, or service delivery models).
Other duties as assigned.
Qualifications
Background: Bachelor’s degree in Data Science, Statistics, Econometrics or a related field (Master’s preferred).
Forecasting Expertise: Direct experience building and validating predictive models (e.g., churn, LTV, demand forecasting) and prescriptive models (e.g., resource allocation, pricing optimization).
Technical Proficiency: Advanced skills in SQL and statistical programming (Python or R). Must have experience building and maintaining BI dashboards.
Data Strategy & Collaboration: Proven ability to work cross-functionally with Engineering/Data Engineering teams to define and refine data structures necessary for complex modeling.
Innovation & AI Mindset: Demonstrated interest and foundational knowledge regarding the application of Agentic AI or advanced machine learning to enhance predictive modeling and business intelligence.
Passion: Twin’s purpose to transform lives by empowering people to reverse, prevent and improve chronic metabolic diseases excites you.
This hybrid opportunity is based out of our New York, NY office. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
Compensation and Benefits The compensation range for this position is $130,000 - $140,000 annually.
Twin has an ambitious vision to empower people to live healthier and happier lives, and to achieve this purpose, we need the very best people to enhance our cutting-edge technology and medical science, deliver the best possible care, and turn our passion into value for our members, partners and investors. We are committed to delivering an outstanding culture and experience for every Twin employee through a company based on the values of passion, talent, and trust. We offer comprehensive benefits and perks in line with these principles, as well as a high level of flexibility for every Twin.
A competitive compensation package in line with leading technology companies
A remote and accomplished global team
Opportunity for equity participation
Unlimited vacation with manager approval
16 weeks of 100% paid parental leave for delivering parents; 8 weeks of 100% paid parental leave for non-delivering parents
100% Employer sponsored healthcare, dental, and vision for you, and 80% coverage for your family; Health Savings Account and Flexible Spending Account options
401k retirement savings plan
We may use technology, including AI tools, to help our recruiting team review applications and identify relevant qualifications. These tools support our recruiters but do not make hiring decisions. All applications are reviewed by members of our hiring team.
As set forth in Twin Health’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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Languages
- English
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