Top Analytics Jobs in NYC, NY

Investigate and reconcile portfolio, benchmark, model, and custodian performance data. Analyze returns, attribution, benchmark logic, and allocation drift to identify discrepancies and root causes. Build Python diagnostics and SQL queries, maintain data-quality dashboards and audit trails, document findings, and collaborate with quant, engineering, portfolio management, and operations teams to implement validation rules and improve performance reporting reliability.

Analyze customer, order, campaign, cohort, and promotional data using SQL, BigQuery, DBT, and Looker. Partner with Growth and Marketing teams to evaluate campaign performance, A/B tests, churn, and customer behavior. Validate marketing data, manage an AI analytics chatbot, formulate hypotheses, and translate findings into visual presentations and strategic recommendations for leadership.

Lead account analytics for media campaigns by developing analyses, insights, recommendations, dashboards, hypotheses, and measurement tests. Partner with media, strategy, creative, and client teams to evaluate campaign, audience, attribution, and business performance. Teach analysts best practices and oversee one to two analysts or senior analysts. Provide consulting support, reporting implementation, client training, and data visualization using SQL, Python, Tableau, and advanced Excel.

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.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.

Ten-week hybrid summer internship supporting data and analytics initiatives across banking teams. Interns will gather requirements, assemble and explore structured and unstructured data, perform analysis, identify trends, create insights and dashboards, collaborate with business partners, communicate findings, and present a capstone project. Assignments may include advanced analytics, reporting, visualization, data mining, automation, root-cause analysis, cohort analysis, and model development.

Graduate data analytics interns support data gathering, cleaning, exploration, analysis, reporting, dashboarding, visualization, and business insight initiatives. They collaborate with mentors and cross-functional teams, investigate trends, communicate findings to stakeholders, refine analytical approaches, and present project outcomes. The 10-week hybrid program is based in Columbus, Johnston, or Boston.

Analyzes web, customer, and campaign data to generate actionable digital marketing insights. Builds dashboards and presentations using Adobe Analytics, Power BI, or Tableau; evaluates site performance, media monetization, A/B tests, and web projects; supports tagging, reporting validation, and vendor implementations. The role partners with stakeholders and Agile teams, manages analytics priorities, and communicates findings to guide marketing strategy and business decisions.

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

Lead data analysis for merchants, manage projects to improve product and acquisition strategies, and communicate insights effectively.

Analyzes business processes and data integration needs, translates stakeholder requirements into technology solutions, and supports delivery from discovery through adoption. Responsibilities include requirements gathering, process analysis, data mapping and validation, migration, testing, stakeholder workshops, vendor coordination, implementation support, and business case development. The role also develops and maintains analytics and automation solutions using Microsoft and other business intelligence platforms.

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.

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.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Lead client-facing analytics implementations across Google Analytics 4, Adobe Analytics, and tag management systems. Responsibilities include designing measurement strategies, auditing digital ecosystems, managing tagging and consent platforms, developing data governance and privacy solutions, analyzing performance, aligning KPIs with business goals, presenting insights, supporting proposals, and improving internal analytics standards. Preferred experience includes server-side tagging, data clean rooms, customer data platforms, experimentation, CRM systems, and ETL tooling.

Own marketing channel performance analysis, reporting, experimentation, dashboards, and measurement frameworks. Develop incrementality, LTV, and forecasting analyses; identify data quality risks; and translate complex findings into actionable recommendations for Marketing, Growth, and Finance stakeholders. The role requires strong SQL, BI reporting, marketing measurement, experimentation, and analytical communication skills, with AI tools used to accelerate analytics workflows.

Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.

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.

Leads data analytics for clinical operations, triaging data issues, identifying root causes, and partnering with engineering, data, customer success, and business teams on scalable solutions. Defines analytical requirements, develops insights and dashboards, communicates findings to technical and non-technical audiences, manages stakeholder relationships, drives improvement initiatives, and may lead a team of data analysts.

Leads research, data analysis, reporting, and data management for film and media incentive programs. Oversees data collection, validation, database maintenance, reporting systems, program evaluation, and industry research. Prepares executive briefings, reports, spreadsheets, and actionable recommendations; tracks production status and incentive structures; improves workflows and data quality; and supports strategic planning, policy analysis, stakeholder engagement, and cross-functional initiatives.

Analyzes digital customer and product data to deliver dashboards, reporting solutions, experimentation measurement, journey analytics, attribution insights, and ad-hoc analysis. Partners with Digital Product and Technology teams throughout the product lifecycle, validates data and tracking solutions, supports platform modernization, performs data quality checks, and translates business questions into scalable business intelligence products while maintaining risk and regulatory controls.

Lead media research, campaign measurement, and analytics supporting sales, marketing, product, and client leadership. Develop audience analyses, benchmarks, case studies, surveys, and market insights; manage measurement vendors; shape advertising measurement capabilities; and serve as the senior client contact for research discussions. Establish analytical rigor, validate methodologies, document assumptions, and design AI-enabled workflows for client measurement challenges.

Analyze loyalty and mobile app data to identify trends, engagement opportunities, retention drivers, and revenue insights. Build and maintain KPI dashboards, conduct ad hoc analyses, validate reporting with cross-functional teams, communicate findings, and optimize scalable data workflows supporting Fanatics ONE and FanaticsApp.