Top Senior Analytics Jobs in NYC, NY

Provides analytics-driven strategic advice for mergers, acquisitions, and other transactions. Responsibilities include analyzing contract data, developing algorithms and predictive models, integrating data sources, building pipelines, creating dashboards, validating data integrity and security, and identifying risks and compliance indicators. The role also involves client collaboration, mentoring junior staff, and delivering data-driven insights using Python and machine learning.

Leads data analytics projects that generate insights for strategic decision-making. Develops visualization solutions with Power BI and Tableau, builds data pipelines, applies statistical modeling and predictive analytics, and manages data integrity and security. Collaborates with clients on tailored data solutions while coaching analytical teams, managing accounts, overseeing project success, and identifying business opportunities.

Leads enterprise lending and installment analytics to optimize portfolio growth, customer value, credit performance, and customer experience. Oversees decisioning frameworks, lifecycle targeting, product economics, experimentation, causal measurement, modeling strategy, reporting, governance, and real-time personalization. Partners with Product, Marketing, Risk, Finance, and Operations while managing and developing a high-performing analytics organization.

Lead digital analytics efforts to define OKRs, run A/B tests, analyze digital customer behavior, and deliver actionable insights to product, tech, and design partners to improve engagement and customer satisfaction.

Analyze large datasets to identify digital fraud trends, develop loss-reduction strategies and business rules, automate fraud alert processes, monitor emerging risks, and present actionable insights to senior leadership. Collaborate with technical and business teams on fraud-fighting products, apply experimentation and machine learning, manage financial impacts, and improve customer experience across digital payment channels.

Own end-to-end analytics for a business-critical function, including data models, pipelines, dashboards, and strategic insights. Partner with stakeholders and Engineering to establish scalable data foundations, guide experimentation and forecasting, and drive evidence-based decisions. The role also involves documenting analyses, shaping the data roadmap, and promoting a data-first culture across Operations, Engineering, Product, and Design.

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.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

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.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

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.

Lead analytics strategy across eCommerce, content, advertising, and live events. Partner with executives to turn complex data into actionable business recommendations, identify opportunities and risks, shape the analytics roadmap, and guide data investments. Manage and develop a team of three analysts while using AI, automation, scripting, statistical analysis, and BI tools to accelerate decision-making and improve business outcomes.

Manage and grow Ashby’s data analytics team while remaining hands-on with analytical work. The role includes hiring and coaching analysts, improving data practices, prioritizing requests, developing specialization, maintaining analytical quality, and guiding responsible AI adoption. The manager will work across raw and modeled data, dbt models, metric definitions, dashboards, and internal data products, partnering closely with business teams in a remote, high-growth B2B SaaS environment.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Leads fraud strategy through trend analysis, root-cause investigation, mitigation recommendations, and fraud-control optimization. Manages and mentors 2–5 fraud analysts, evaluates detection tools and data sources, monitors performance metrics, and communicates risk insights to leadership. Partners with Operations, Compliance, Credit, and Product teams to implement compliant fraud strategies and reduce losses while supporting growth.

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 the analytics function and Strategic Insights Analysts, owning the analytics roadmap, KPI standards, self-service Looker strategy, and AI-driven automation. Partner with Product, Clinical Operations, Marketing, and Finance executives to prioritize analyses and guide strategic decisions. Build scalable operating models, deploy AI agents and LLM pipelines, improve data quality and monitoring, mentor the team, and translate complex analysis into actionable recommendations. The role requires onsite work in New York City four days per week.

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.

Deliver transaction-focused data analytics for M&A engagements: extract, clean, model, and visualize large financial, customer, sales, pricing, and operational datasets using Python, Alteryx, SQL, and BI tools. Provide actionable insights on revenue, margin, profitability, and value-creation, communicate recommendations to clients, manage workstreams, mentor juniors, and support transaction lifecycle activities.

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

Design and implement continuous enterprise risk-control monitoring across credit, fraud, operational, and compliance domains. Develop AI agents, anomaly detection, root-cause analysis, predictive models, and risk-mitigation tools. Maintain AI and model-risk inventories, build dashboards tracking key risk indicators, and communicate analytical insights to senior stakeholders. Collaborate with Engineering, Data, Compliance, Operations, Identity, and Product teams to instrument risk telemetry and maintain human oversight of automated outputs.

Analyze global performance marketing campaigns, measure media-spend impact, develop data-driven user-growth strategies, define marketing KPIs, and transform complex data into actionable insights. The role partners with data science and marketing technology teams, shapes backend data design, and builds dashboards in tools such as Tableau. Candidates need strong SQL, marketing analytics, data visualization, communication, and analytical skills, with occasional statistical programming experience preferred.