Top Senior Data Analyst Jobs in NYC, NY

Provides data analytics consulting for enterprise clients using Dynatrace observability, digital experience monitoring, and business analytics data. Manages client relationships, performs ad hoc analysis, creates reports and dashboards, presents findings to technical and executive audiences, configures tools, trains users, and influences product improvements. The role translates complex performance and engagement data into strategies that improve digital experiences and business outcomes.

Analyze Experian portfolio repayment performance, credit risk, underwriting and credit-limit changes, collections, funnel metrics, cohort LTV, and unit economics. Own partner analytics models, data definitions, reporting, alerting, and data quality monitoring. Collaborate with Product, Engineering, Partnerships, Finance, and Experian to guide roadmaps, evaluate experiments, identify risks, and support business reviews.

Own end-to-end client reporting and analysis, including scoping, delivery, automated report development, and deep-dive investigations. Partner with client-facing teams to answer complex healthcare questions, improve report efficiency and accuracy, develop scalable reporting automation with data engineering, and establish best practices for visualization, documentation, metrics, and stakeholder communication.

Advances enterprise data governance by maintaining metadata, glossaries, taxonomies, catalogs, lineage, and stewardship workflows. Supports data classification, quality checks, lineage validation, and governance policies while partnering with data product managers, business SMEs, and engineers. Drives adoption through training and playbooks, contributes to Agile delivery using Jira, and helps improve data discoverability, compliance, and trust across the organization.

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

Senior Data Analyst responsible for integrating sales, CRM, customer, campaign, product usage, and engagement data into forecasts, dashboards, recurring reports, datasets, and actionable insights. The role analyzes pipeline performance, customer health, product adoption, retention, churn, marketing campaigns, and commercial trends. It partners with cross-functional stakeholders, defines KPIs, improves data quality, prepares executive reporting, and supports strategic decision-making through clear analysis and recommendations.

Own data center OpEx and power planning, forecasting, budgeting, variance analysis, financial reporting, scenario modeling, and cost optimization. Build complex operational and financial models, develop dashboards, and provide actionable insights to executive leadership. Partner cross-functionally with data center operations, capacity planning, power and sustainability, and sales teams to support strategic decisions and business growth.

Develop and optimize advanced SQL transformations, stored procedures, ETL workflows, and data-quality processes for large Medicaid claims and health-related social needs datasets. Build reproducible, documented data pipelines; calculate healthcare quality, equity, and disparity metrics; conduct code reviews; and collaborate with stakeholders to turn complex data into visualizations and policy insights.

Own monetization analytics across mobile apps and web properties, including subscription, advertising, in-app purchase, and partner-offer revenue. Build reliable datasets and pipelines, manage revenue metrics, analyze pricing and paywall experiments, model LTV and cohorts, evaluate ad monetization, reconcile revenue sources, and support forecasting and prioritization. Communicate insights to Monetization, Product, and business leaders to drive revenue growth and measurable impact.

Own user acquisition analytics across mobile apps and web properties, measuring channel performance, attribution, retention, LTV, ROAS, and payback. Build datasets, pipelines, dashboards, cohort analyses, and predictive models; reconcile MMP, ad network, and internal data; investigate anomalies and fraud; analyze funnels; design incrementality and A/B tests; and recommend budget allocation and channel strategies to the UA team.

Conduct end-to-end analysis of complex healthcare data, including medical and pharmacy claims. Build and maintain SQL queries and analytical datasets, create visualizations, document methodologies, validate data, and translate findings into actionable business recommendations. Collaborate with analysts, data scientists, underwriters, product teams, account management, and cost-containment stakeholders to operationalize sustainable analytics solutions.

Analyze and document raw healthcare data ingestion into the Bronze layer of a medallion data architecture. Responsibilities include data mapping, lineage documentation, quality monitoring, schema-drift detection, ingestion troubleshooting, and data-health dashboard development. The role collaborates with engineering and analytics teams to improve data accuracy, traceability, and operational excellence across large healthcare datasets.

Analyze and transform cloud data using SQL, dbt, and Google Cloud; build automated pipelines, data visualizations, validation checks, unit tests, monitoring, and alerts. Partner with engineering teams and enterprise insurance clients to improve data quality, governance, automation, and decision-making. Communicate insights clearly, document technical work, develop insurance domain expertise, and contribute to collaborative reviews and on-call support.

Leads analytics strategy for Zip’s emerging financial products, from market sizing and launch readiness through adoption, retention, risk, and unit economics. Partners with Product, Finance, Risk, and Operations leaders to define metrics, build scalable dbt models and reporting frameworks, analyze customer and portfolio behavior, and guide strategic decisions. Establishes SQL and analytics standards, mentors analysts, and translates complex findings into recommendations for executives.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.

Lead data strategy and execution for emerging sectors, transforming large consumer datasets into accurate, scalable client insights. Responsibilities include resolving data-quality issues, designing workflows, maintaining sector taxonomies, partnering with product, revenue, engineering, and insights teams, and coaching analysts. The role requires hands-on analysis, production-grade data workflow development, stakeholder communication, and ownership of quality standards and methodologies in a rapidly evolving environment.

Analyze product, program, member, client, and operational data using advanced SQL in Databricks. Define KPIs and measurement frameworks, conduct segmentation and root-cause analysis, validate datasets, develop reporting, and translate findings into actionable recommendations. Partner with Product, Engineering, Operations, Client Success, and business leaders to improve performance and support strategic decisions.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

Drive growth and product decisions through experimentation, statistical analysis, metrics management, data pipelines, modeling, and dashboard development. Partner with business and product teams to answer analytical questions, build ingestion and transformation workflows with dbt, and create visualizations that enable stakeholders to explore data and act on insights.

Build and maintain scalable batch and real-time data pipelines for financial and alternative datasets. Productionize AI/ML workflows for document extraction, classification, and data processing; own model evaluation, monitoring, and human review. Design investment data models, validation, anomaly detection, and reconciliation systems. Partner with quants and data scientists to operationalize research signals, onboard vendors and datasets, integrate APIs, and improve data reliability using modern cloud, streaming, orchestration, and warehouse technologies.

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.

The Senior Data Analyst supports Risk Management and Compliance reporting by collecting, validating, analyzing, and modeling data. The role develops dashboards, reports, visualizations, governance practices, and automation using SQL, Excel, Power BI, SSAS, and VBA. Responsibilities include data quality management, systems testing, requirements documentation, UAT support, executive presentations, risk insights, stakeholder collaboration, process improvement, and mentoring junior analysts.

Leads clinical pharmacy program analytics by defining governed clinical logic, building SQL transformations and curated datasets, designing outcome evaluations, and creating Power BI and Sigma dashboards. Translates pharmacy guidelines, claims, and drug reference data into reliable metrics, validates predictive models, manages data quality, and ensures HIPAA-compliant data use. Communicates insights to clinical, executive, client, and pharmaceutical audiences while mentoring analysts and supporting program design and continuous improvement.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Lead end-to-end analytics: own KPIs and dashboards, define measurement with stakeholders, build scalable pipelines with Data Engineering, run deep-dive analyses, close reporting gaps, and advocate best practices in visualization, documentation, and metric consistency to inform business strategy.