Top Tech Jobs & Startup Jobs in NYC, NY

This is a talent-pool submission inviting candidates to share their background and role preferences. Profiles enter Garner's candidate pool for recruiter review; recruiters will contact matches when relevant roles open. Includes fraud/security notice about official email domains and an equal employment opportunity statement with accommodation contact information.

Lead product strategy and roadmap for member-facing Incentive Experience, build scalable reimbursement operations, embed with users and ops teams, drive features from discovery through launch, and define success metrics to measure outcomes.

The Director of Insights will transform healthcare data into industry insights, drive storytelling, and support marketing initiatives to enhance Garner's brand and demand generation.

The Senior Applied Scientist will develop and optimize algorithms for evaluating healthcare providers, focusing on quality, cost, and access, and will work closely with engineering to implement scalable solutions.

The role involves automating operational workflows, building API-driven systems, managing integrations, and applying infrastructure-as-code to enhance healthcare operations.

Manage the Data Platform Team, focusing on high-throughput data infrastructure and AI-native development. Oversee data processing systems, mentor engineers, and align team goals with business objectives.

Join the Engineering team to develop AI-driven software for analyzing vast amounts of medical data, ensuring security and privacy. Collaborate across disciplines and contribute to innovative healthcare solutions.

Own and architect Garner's production ML platform, ensure reliability, performance, cost-efficiency, implement ML CI/CD, drift monitoring, observability, and set standards for future MLOps team.

As a Senior Software Engineer, lead technical strategy, build AI-optimized systems, mentor engineers, and ensure data privacy and security.

Design, build, and own algorithmic systems that evaluate providers, make recommendations, and optimize outcomes across cost, quality, and access. Define objective functions and metrics, run experiments, deploy scalable production models, and iterate based on real-world healthcare outcomes while collaborating closely with engineering and business stakeholders.