Business Analytics Lead - Predictive Modeling at Twin Health

New York, New York, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Health Tech, Digital HealthIndustries

Requirements

Bachelor’s degree in Data Science, Statistics, Econometrics or a related field (Master’s preferred)
Direct experience building and validating predictive models (e.g., churn, LTV, demand forecasting) and prescriptive models (e.g., resource allocation, pricing optimization)
Advanced skills in SQL and statistical programming (Python or R)
Experience building and maintaining BI dashboards
Proven ability to work cross-functionally with Engineering/Data Engineering teams to define and refine data structures necessary for complex modeling
Demonstrated interest and foundational knowledge regarding the application of innovation & AI mindset

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

Skills

Predictive Modeling

Business Analytics

Digital Twin

Data Analysis

Metabolic Health

CGM

Machine Learning

Statistical Modeling

Healthcare Analytics

Twin Health

Monitors and treats chronic metabolic diseases

About Twin Health

Twin Health focuses on addressing chronic metabolic diseases by targeting their root cause: damaged metabolism. The company operates in the healthcare and wellness market, specifically for individuals suffering from conditions like diabetes and Metabolic Syndrome. Twin Health uses its Whole Body Digital Twin technology, which combines sensors, artificial intelligence, and medical science to create a virtual model of the human body. This technology allows for real-time monitoring and analysis of a person's metabolic functions, enabling the creation of personalized treatment plans. Unlike its competitors, Twin Health emphasizes reversing and preventing these diseases through a subscription-based model that provides continuous support and updates. The goal of Twin Health is to effectively manage and reduce the prevalence of chronic metabolic diseases, improving the health of millions globally.

Mountain View, CaliforniaHeadquarters

2018Year Founded

$227.1MTotal Funding

LATE_VCCompany Stage

AI & Machine Learning, HealthcareIndustries

501-1,000Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Unlimited Paid Time Off

Parental Leave

Health Savings Account/Flexible Spending Account

Company Equity

Remote Work Options

Flexible Work Hours

Risks

Competition from companies like Virta Health threatens Twin Health's market share.

Privacy concerns and regulatory scrutiny challenge wearable technology data collection.

Economic downturn may impact consumer spending on health subscriptions, affecting revenue growth.

Differentiation

Twin Health's Whole Body Digital Twin offers real-time metabolic monitoring and personalized treatment.

The platform integrates AI, sensors, and medical science to reverse chronic diseases.

Twin Health targets root causes of metabolic diseases, unlike competitors focusing on symptoms.

Upsides

Growing digital twin market offers strong potential for Twin Health's technology.

Increasing trend in personalized medicine aligns with Twin Health's treatment approach.

AI-driven solutions adoption by healthcare providers enhances collaboration opportunities for Twin Health.

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