Top Senior Analytics Jobs in NYC, NY

Lead pricing analytics for GoodRx Companion subscription: build forecasting and elasticity models, optimize pricing to drive signups and unit economics, create dashboards and reports, analyze fill patterns, and deliver actionable insights to cross-functional stakeholders to improve program performance.

Lead and scale a casino analytics team to drive data-informed strategy, experimentation, and reporting. Partner with product, data science, and operations to deliver executive insights, build analytical frameworks, and develop high-performing analysts to unlock growth and operational efficiency.

Lead complex data analysis for private equity and corporate deals across diligence, post-deal, and exit phases. Use advanced analytics, predictive modeling, and visualization tools to generate insights, improve data quality, collaborate with stakeholders, and coach teams to deliver strategic, data-driven recommendations at deal speed.

As a Decision Analytics Consultant, you'll leverage RWD and RWE analytics to support pharmaceutical clients by generating insights and conducting analyses for evidence generation and HEOR studies.

The Staff Data Scientist will drive data-informed monetization strategies across subscriptions, advertising, and virtual currencies, collaborating with product and engineering teams and defining success metrics.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

Lead data analysis projects to help merchant partners understand Upside's impact, manage analytics relationships, and improve product strategy.

The Senior Manager, Risk Analytics will build and own Upstart's risk analytics program, managing Key Risk Indicators, data models, and reporting infrastructure for enterprise-wide risk monitoring and compliance. They will collaborate with risk owners and conduct data aggregation and reporting, supporting risk assessments and regulatory requirements.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

Perform financial due diligence data analytics for middle-market M&A: obtain, validate, normalize, analyze transaction data (revenue, costs, inventory), produce dashboards and visualizations, identify trends/outliers, and communicate insights to deal teams and clients.

Maintain databases and dashboards, clean and compile large media and syndicated datasets, QA data, run queries and ETL-related tasks, analyze data to generate insights and visuals, respond to ad-hoc data requests, automate repetitive processes, and collaborate across teams to deliver timely, error-free client reporting and recommendations.

The Associate Director will manage a team, develop statistical models for marketing analytics, and cultivate client relationships to drive business results.

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.

As the Senior Fraud Strategy and Analytics Manager, you will analyze fraud trends, build predictive fraud models, implement prevention rules, and enhance risk profiles while collaborating with cross-functional teams in the financial services sector.

The Senior Data Scientist will lead revenue-driving initiatives, optimize strategies, enhance data analysis techniques, and improve data pipelines for maximum revenue impact.

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.

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.

The Senior Analytics Specialist develops processes for digital optimization and collaborates on A/B and multivariate testing through data insights.

Embedded on a core business team, own analytics end-to-end: define problems, build reports and experiments, analyze data, surface insights, and drive recommendations that influence product, growth, AI/automation, or partnership decisions.

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.

Lead digital measurement and analytics for ecommerce: build measurement frameworks, run attribution and predictive models, drive A/B testing and personalization, produce executive dashboards and actionable insights, partner cross-functionally to improve conversion, retention, and LTV.

This role involves conducting advanced data analysis to drive strategic decisions, defining metrics, collaborating with teams, and improving performance through insights.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Associate will support portfolio analytics, focusing on evergreen vehicles and asset-level analyses to inform investment decisions and enhance portfolio management. Responsibilities include data-driven insights, risk analysis, and collaboration across firm teams to optimize performance and liquidity pacing.

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.