About the job
At Garner Health, we are on a mission to revolutionize the healthcare economy by delivering high-quality and affordable care for everyone.
We are fundamentally reshaping the way healthcare operates in the U. S. by collaborating with employers to redesign healthcare benefits through transparent incentives and robust, data-driven insights. Our innovative approach empowers employees to access higher-quality, lower-cost care, creating a system that benefits all stakeholders. Patients experience improved health outcomes, employers utilize healthcare funds more effectively, and physicians are acknowledged for providing outstanding care instead of merely increasing the number of procedures performed.
Garner is among the fastest-growing healthcare technology companies in the nation. Our products are trusted by the most discerning employers and providers in the industry, and we are assembling a team of talented, mission-driven professionals who are eager to create a significant impact on healthcare at scale.
About the Role:
We are in search of an exceptional Data Scientist II to join our Central Data team. Reporting to the Director of Data Science & Analytics, this pivotal role is crucial in shaping Garner’s Product & Growth strategy, from assessing product impact to developing models that drive user engagement. You will work in tandem with data, product, and engineering teams to enhance the effectiveness of Garner’s member-facing product by addressing questions such as, “Which features drive user engagement?”, “What is the optimal time and channel for member outreach?”, and “What data concepts must we expand to better understand what motivates members to engage with Garner?” Your contributions will have a direct influence on our member-facing products and guide strategic product decisions.
Where You Will Work:
This position is based in our New York City office, with a requirement to work on-site three days a week (Tuesday, Wednesday, and Thursday).
Your Responsibilities:
- Identify and evaluate product success through goal setting, A/B testing, forecasting, and monitoring key product metrics to discern trends.
- Oversee projects from inception to completion, including problem definition, implementation, validation, and iteration.
- Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions, including AI and machine learning models.
- Collaborate cross-functionally with data scientists, product leaders, engineering, and operations teams to define metrics and success criteria.
