Top Senior Analytics Jobs in NYC, NY

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 strategic deposit pricing analytics focused on CDs, elasticity testing, deposit trends, yield-seeking behavior, and macroeconomic impacts. Serve as the subject-matter expert on CD data, translate findings into executive presentations, build automated self-service dashboards, and partner with finance, pricing, marketing, risk, product, and branch teams. Monitor competitor pricing and economic trends to inform retail banking product decisions.

Analyze complex data, build self-service data solutions, and develop business intelligence tools, metrics, dashboards, and visualizations. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, definitions, security, and access governance. The role requires scripting, data querying, Snowflake development, business intelligence visualization, and experience with data management and governance.

Conduct quantitative research and pricing analytics for credit card installment products. Apply statistical modeling, econometrics, hypothesis testing, causal inference, and experimentation to evaluate pricing strategies, customer behavior, profitability, and policy effectiveness. Build scalable analytics processes, communicate insights to senior stakeholders, and partner with Finance and Marketing. Lead and develop analytics talent while evaluating responsible applications of artificial intelligence and automation.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

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.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

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

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

Own CRM analytics, reporting, segmentation, attribution, and data quality for email, push, in-app, and SMS across multiple FOX brands. Write and troubleshoot SQL against Snowflake/Braze, build attribution models, audit segments, support experimentation, and deliver insight-driven executive summaries to marketing and editorial stakeholders.

Own the end-to-end analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, surface insights, and drive recommendations through execution. Partner with product, growth, finance, and operations leaders to influence decisions and improve key business outcomes.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface actionable insights; influence leadership decisions; and drive initiatives through execution. The role requires first-principles problem solving, strong data skills, persuasive communication, and end-to-end ownership of ambiguous business problems.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Direct advanced analytics for a marketing agency, leading a team that develops statistical models, marketing mix models, attribution algorithms, campaign tests, and ROI analyses. Manage client engagements, mentor analysts, improve analytical methodologies, productionize models, and collaborate with business intelligence and data engineering teams. Translate complex technical findings into actionable business recommendations while supporting media optimization and marketing effectiveness initiatives.

Use data analytics to identify and reduce operational risk across EP & TBM. Analyze large datasets, perform root cause analysis, recommend scalable process improvements, build dashboards and visualizations, measure initiative effectiveness, automate reporting, and partner with engineering, product, and risk teams to prioritize and implement risk reduction.

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.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Support regulatory reporting by analyzing trade and customer account data, responding to regulator and customer inquiries, identifying data anomalies, improving reporting processes, implementing AI/ML automation, and ensuring data governance, quality control, and acceptance testing for reporting systems.

Provide quantitative analytics and reporting for private credit portfolios (Direct Lending, Asset-Based Finance, Structured Credit). Build and automate models, dashboards, and data workflows; validate and reconcile investment data; support underwriting, portfolio monitoring, risk oversight, and senior reporting; collaborate with investment, risk, finance, operations, and technology teams.

Support US Options pricing and strategy through data analytics, statistical modeling, dashboarding, and forecasting. Evaluate client trading patterns, monitor competitive and regulatory developments, manage pricing change processes, and provide actionable insights to Sales and senior stakeholders across Derivatives and Futures.

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.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.