Top Healthtech Data & Analytics Jobs in New York City, NY

Design and apply advanced statistical models and custom analyses using R, Tableau, SAS, Visual Basic and Excel to inform client decisions. Synthesize and present findings, create deliverables, manage project status, build client relationships, mentor associates, and implement solutions while contributing to ZS's analytic capabilities.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

The Senior Data Analyst will partner with clinics to analyze financial performance and operational efficiency, design reports, and communicate insights effectively.

The Senior Analytics Engineer will build and scale the analytics layer for decision-making. Responsibilities include design, implementation, testing, and maintaining data reliability across teams.

As a Data Analyst, you will analyze and report on large datasets, ensure data quality, automate deliverables, and provide insights to drive decisions within the Finance team.

The Director of Patient Services Analytics will deliver data-driven insights and solutions for patient services in Oncology and Primary Care, collaborating with various teams to improve programs and drive strategy decisions.

The Senior Data Engineer will build and maintain data pipelines, optimize data processes, design a data validation framework, and ensure user privacy and security.

The Senior Manager, Data Science - Patient Growth will own the marketing analytics strategy and lead a data science team focused on improving patient acquisition through data-driven measurement and growth analytics.

Lead the implementation of evaluation frameworks for AI systems and clinical assessments, translate clinical evaluations into rubrics, and supervise a team of analysts and engineers.

The Senior Data Engineer will own and evolve data pipelines, collaborate with teams for data models and pipelines, optimize ETL processes, and implement data storage solutions.