
501 - 1000 employees
Founded 2014
⚕️ Healthcare Insurance
🧘 Wellness
☁️ SaaS
Healthcare Insurance • Wellness • SaaS
Vida Health is a company committed to improving health outcomes for various physical and mental health conditions, including diabetes, obesity, depression, and hypertension. They offer personalized, human-led care combined with digital technology to manage and treat these complex conditions. Vida Health partners with employers, health plans, and consultants to provide comprehensive health solutions. Their services include video chats and text-based messaging with healthcare providers, and they utilize machine learning and synced devices to personalize member care. They focus on significant cost savings and improved health outcomes for cardiometabolic conditions, guaranteeing results and offering up to 100% of fees at risk for both physical and mental healthcare.
🔥 3 minutes ago
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501 - 1000 employees
Founded 2014
⚕️ Healthcare Insurance
🧘 Wellness
☁️ SaaS
Healthcare Insurance • Wellness • SaaS
Vida Health is a company committed to improving health outcomes for various physical and mental health conditions, including diabetes, obesity, depression, and hypertension. They offer personalized, human-led care combined with digital technology to manage and treat these complex conditions. Vida Health partners with employers, health plans, and consultants to provide comprehensive health solutions. Their services include video chats and text-based messaging with healthcare providers, and they utilize machine learning and synced devices to personalize member care. They focus on significant cost savings and improved health outcomes for cardiometabolic conditions, guaranteeing results and offering up to 100% of fees at risk for both physical and mental healthcare.
• Take the questions that growth, strategy, and clinical teams need answered and design, plan, and execute the health-outcomes analyses that answer them, using biometric, claims, and clinical data for both internal and external audiences. • Apply modern AI tools (e.g., LLM-based assistants) in your day-to-day workflow to accelerate literature review, analysis, code, and manuscript drafting, with demonstrated proficiency, not just familiarity. • Conduct literature reviews, run the analyses, and prepare manuscripts for peer-reviewed journals and clinical white papers, carrying work from concept to submission. • Apply methods such as multilevel/mixed-effects modeling, survival analysis, case-control difference in difference, budget impact analysis, and clustering (e.g., K-means, DBSCAN) to complex, time-series, and nested data structures. • Partner with growth, strategy, and clinical teams to generate the economic and clinical evidence that supports enterprise sales, client retention, and value-based care contracting. • Work fluently with medical and pharmacy claims to quantify utilization, cost, and savings outcomes. • Monitor pipelines for measurement fidelity and quality, and curate and prepare biometric, claims, and clinical data for analysis. • Coordinate evidence and reporting projects across product, marketing, engineering, and business development, providing the project-management structure that keeps multi-stakeholder work on track. • Additional responsibilities as needed.
• Bachelor's degree required. • 5-7+ years of hands-on experience in clinical analytics, HEOR, health economics, digital health, or a related domain. • Demonstrated, hands-on experience analyzing healthcare claims data and applying rigorous statistical methods required. • High proficiency in at least one statistical package: Python (preferred) or R; fluency in SQL. • Startup/growth-stage experience; equivalent scrappy operating experience within a larger org also works. • Comfortable sourcing your own data and delivering rigorous work without the infrastructure, resources, or processes of a large organization • Experience with time-series and nested/longitudinal data. • A record of peer-reviewed publications or research projects, ideally in digital health, telemedicine, or value-based care. • Proven ability to take a business question and independently carry it to a published result: scoping, analyzing, and delivering with minimal oversight. • Demonstrated, hands-on proficiency using AI tools (e.g., LLM-based assistants) to do analytical and writing work more efficiently and to a higher standard. • Ability to translate technical findings into clear, persuasive insight for non-technical executives, commercial, and external audiences. • Familiarity with HIPAA and data-privacy requirements as they relate to PHI and digital health.
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