Top Analytics Jobs in NYC, NY

Own the experimentation strategy for FanDuel’s generosity portfolio, prioritizing tests, guiding experiment design and analysis, translating insights into business decisions, and partnering with commercial, marketing, and data science teams. Lead and develop analysts, maintain statistical rigor, support experimentation tooling, and communicate recommendations to leadership. The role requires advanced experimentation methods, quantitative analysis, SQL, Python, Databricks, and strong stakeholder and people leadership skills.

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.

Leads product analytics for Retail Bank growth, using SQL, Python, R, experimentation, causal inference, statistical modeling, segmentation, and data storytelling. Partners with Product, Engineering, Finance, and Research to shape roadmaps, prioritize opportunities, establish KPI standards, and influence investment and product decisions.

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.

Supports healthcare implementation projects, business workflow documentation, process improvement, work plans, and deliverables. Reviews large datasets from multiple sources to identify outliers, monitor trends, and prepare state-mandated reports. The internship provides experiential learning for undergraduate students interested in healthcare or data analytics.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

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.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern 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 advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

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.

As a Decision Analytics Associate Consultant, you will develop statistical models, apply analytic techniques, and communicate results to clients. You will also design custom analyses and guide team projects while mentoring Associates and maintaining client relationships.

Provide quantitative analytics consulting to clients by defining business information needs, identifying appropriate data, executing analytical plans, evaluating results, and communicating actionable findings. The role requires collaboration with clients, expertise in advanced modeling and analytics tools, familiarity with client processes, and the ability to lead teams and advise senior decision-makers.

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 advanced econometric, microsimulation, forecasting, causal inference, and policy-impact modeling for NYC policies and investments. Develops reproducible R-based analytical workflows, validates models, analyzes complex datasets, and communicates findings to technical and nontechnical stakeholders. Oversees complex research projects, mentors staff, collaborates with agencies and external partners, and translates quantitative results into policy recommendations.

Analyze and optimize marketing campaign ROI across channels, evaluate app and partner data, conduct funnel, cohort, attribution, and retention analyses, and develop actionable recommendations. The role requires Marketing Mix Modeling, Multi-Touch Attribution, forecasting, segmentation, and statistical analysis. The consultant will collaborate with product, analytics, engineering, and marketing stakeholders to define measurement strategies, build reporting mechanisms, and translate complex data into business insights that improve adoption, retention, revenue, and campaign effectiveness.

This internship develops quantitative analytics and financial engineering solutions for BlackRock’s Aladdin platform. Responsibilities include building financial risk models, applying quantitative techniques to investment and client-business problems, developing Python-based solutions, delivering actionable analytics, and collaborating with investment and business teams. Interns gain experience in financial markets, investment products, quantitative research, technology, and the Aladdin platform.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Leads marketing and sales analytics strategy, architecture, and measurement. Builds data models, pipelines, machine learning datasets, attribution and incrementality models, and revenue-performance analyses. Advises leaders on investments, tools, account prioritization, and funnel economics. Establishes data, metric, testing, and privacy standards; partners with Marketing, Sales, Finance, Revenue Operations, Data Engineering, and IT; plans roadmaps; presents recommendations to executives; and mentors analysts and engineers.

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.