Top Senior Analytics Jobs in NYC, NY

Leads data analytics strategy, modeling, testing, reporting, and process improvements across business units. Mines complex databases, evaluates products and processes, improves operational efficiency, and consults on data systems. Manages and mentors junior analysts while supporting projects through the full lifecycle. The role emphasizes business intelligence, programming, strategic analysis, and collaboration in a fast-paced environment.

Analyze transaction, financial, and operational data for deals diligence engagements. Build data models, dashboards, and visualizations; apply Python, SQL, statistical methods, and analytics tools to interpret large datasets. Identify trends, test assumptions, validate data quality, document findings, and support client recommendations. Manage workstreams, collaborate with senior team members, adapt to transaction timelines, develop deal context, and mentor junior analysts.

Analyze complex marketing and customer datasets to produce actionable insights, executive dashboards, recurring reports, and campaign performance analyses. Define metrics, evaluate trends, communicate findings to senior leaders, and partner cross-functionally to support growth and improve marketing outcomes. Independently manage analytical workstreams, optimize processes, and develop data products incorporating artificial intelligence and large language models.

Develop data models, queries, reports, and analytics for commerce enablement, controls, risk, and regulatory functions. Translate business needs into high-quality datasets and meaningful descriptive, diagnostic, predictive, and prescriptive insights. Partner with product, data management, strategy, technology, and analytics teams to define metrics, automate recurring reporting, rationalize complex data, and present findings to stakeholders for decision-making.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, segmentation, and LTV analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and deliver actionable recommendations. Requires strong SQL and Python skills, causal measurement expertise, marketing platform experience, and the ability to communicate insights to senior stakeholders.

Own the analytics lifecycle from complex raw data through executive-ready insights. Design experiments, analyze performance drivers, build scalable data pipelines and analytical frameworks, and communicate findings to marketing, product, and technology stakeholders. The role supports customer acquisition, owned media optimization, repeatable reporting, and roadmap decisions through secure, maintainable SQL and Python or R solutions.

Leads quantitative and qualitative Medicaid policy research from project scoping through dissemination. Oversees data acquisition and analysis, monitors state and federal policy changes, develops briefs and presentations, conducts stakeholder interviews, supervises research staff, manages external collaborators, and translates findings into actionable recommendations for policymakers, providers, advocates, and the public.

Own measurement strategy and instrumentation quality for web and mobile initiatives. Translate business goals into tagging specifications, KPIs, event schemas, and acceptance criteria; partner with marketing, product, engineering, and analytics teams; validate releases; troubleshoot tracking issues; govern data standards; and ensure behavioral data produces reliable, analytically accessible datasets and reporting.

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.

Support digital product analytics for an application status platform by defining measurement strategies, KPIs, analytical frameworks, dashboards, governed datasets, and anomaly alerts. Analyze platform data, identify trends and performance issues, communicate recommendations to product and technology stakeholders, and collaborate on instrumentation and pipelines. Use AI-enabled tools to accelerate validated analysis while building reusable playbooks and scalable self-service reporting capabilities.

Leads digital marketing analytics strategy through quantitative research, experimentation, causal measurement, and customer behavior analysis. Partners with Marketing, Finance, Product, and Technology to convert insights into business actions. Builds and manages a high-performing analytics team, establishes scalable processes, evaluates AI-enabled workflows, and optimizes marketing performance through statistical methods, A/B testing, multivariate experiments, and profit-and-loss analysis.

Leads credit card acquisition analytics for U.S. consumer and small business portfolios. Manages data scientists and analysts, develops predictive models, evaluates marketing campaigns, shapes offer and targeting strategies, and translates customer and channel insights into measurable business outcomes. Partners with product and marketing leaders, communicates findings to senior stakeholders, and promotes experimentation, model governance, scalable reporting, and continuous improvement.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Lead analytics for a corporate real estate portfolio, integrating financial, headcount, occupancy, and property data. Build scenario and financial models for capital allocation, expense planning, and portfolio strategy. Conduct ad hoc analyses, improve data workflows and data quality, and translate complex findings into concise executive presentations and strategic recommendations for senior leadership.

Leads people analytics initiatives covering workforce planning, retention, recruiting, engagement, organizational effectiveness, and productivity. Develops executive dashboards and KPI frameworks using workforce and business data, delivers diagnostic and predictive analyses, ensures data governance, and translates findings into actionable recommendations for HR and business leaders. Partners cross-functionally to improve reporting, analytics infrastructure, and data-driven decision-making.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver insights that influence decisions and key performance indicators. Partner with product, growth, finance, and operations leaders to communicate recommendations and drive initiatives through execution.

Build network, demand, pricing, and partner analytics for specialty pharmacy and infusion networks. Develop claims-based prevalence, volume, geographic capacity, pricing, routing, and impact models; create scalable tools with Engineering; automate analyses using AI; support enterprise sales with client-specific insights; and provide executive recommendations on pricing, partnerships, and growth.

Develops credit card analytics strategies to grow partner relationships and customer engagement. Integrates and analyzes large data sets, applies statistical techniques and predictive modeling, builds secure data environments, evaluates measurement tools, and delivers actionable insights. Leads dashboard and performance metric development while collaborating with marketing, product, analytics, vendors, and other cross-functional teams.

Owns go-to-market metrics, dashboards, forecasting analytics, churn and propensity modeling, pipeline analysis, and executive reporting. Partners with Finance, Product, RevOps, and Data Engineering to establish trusted source-of-truth data, improve QBR and forecast processes, automate reporting, and connect product usage to revenue outcomes. Leads and develops a small analytics team while remaining hands-on with complex analytical problems and AI-enabled workflows.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

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.

Leads analytics and AI initiatives for North American underwriting teams, translating business needs into analytical requirements and practical solutions. Performs hands-on analysis of complex datasets, recommends appropriate analytical methods, prototypes AI-enabled solutions, and partners with data, technology, and business teams through agile delivery. Communicates findings to technical and nontechnical stakeholders, supports model deployment and monitoring, ensures governance and explainability, and drives measurable adoption and business outcomes.

Analyzes large-scale pharmacy claims data using SQL to validate adjudication, pricing, benefits, reimbursements, and contractual compliance. Investigates discrepancies, performs root-cause analysis, quantifies financial and operational risk, supports audits and reconciliations, and develops monitoring, dashboards, reports, and analytical tools. Partners with Finance, Legal, Product, Operations, Network, and Compliance teams to improve claims accuracy, automate controls, and communicate actionable findings.

Leads deployment and integration of actuarial models into digital products. Manages delivery planning, coordinates analytics and development teams, establishes governance and testing frameworks, guides product design, explains methodologies and model outputs to technical and executive stakeholders, and supports client relationships and growth. Requires strong quantitative modeling, digital product development, communication, project management, and stakeholder engagement skills.