Top Senior Analytics Jobs in NYC, NY

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead supply-and-demand forecasting for the psychiatry service line: build and maintain S&D models, integrate models into core data infrastructure, define operational metrics (capacity, clinician utilization, hiring targets), run forecast vs. actual audits, and partner cross-functionally to guide hiring, resource allocation, and operational improvements.

Analyzes healthcare claims, provider, reimbursement, and financial data to support out-of-network dispute negotiations, arbitration, QPA accuracy, and IDR performance. Builds SQL-based reports, dashboards, data processes, metrics, and financial views; validates data quality; integrates internal and external sources; identifies trends and risks; and presents actionable recommendations to leadership and cross-functional stakeholders.

The Staff Data Scientist will work with product teams to analyze data, identify improvement opportunities, design experiments, and create reporting dashboards to enhance contract management workflows.

Lead end-to-end strategic projects to optimize health plan programs, perform data-driven analyses, build impact models, present executive recommendations, advise cross-functional stakeholders, mentor junior analysts, and monitor initiative outcomes to improve efficiency and care quality.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead market access deal analytics by developing data-driven solutions for payer strategy and reimbursement optimization, conducting claims data analyses, and integrating analytics into pricing strategies. Required to manage healthcare datasets and develop predictive models.

Analyze and reconcile enrollment and member data across Medicaid, Medicare, Marketplace, and Duals. Build reports and dashboards, fix data issues, apply statistical techniques, consolidate disparate sources, and partner with operations to ensure accurate coverage and regulatory compliance.

Lead implementations and ongoing analytics consulting for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train client data teams, and inform product improvements based on customer feedback and domain expertise.