Top Data Analyst Jobs in NYC, NY

Own people-data pipelines, organizational mapping, resource reporting, data transformations, reconciliations, and automated internal tools for Engineering, Product, and Design. Support headcount and resource planning, operating calendars, software capitalization, data governance, executive dashboards, and ad hoc workforce analysis. Partner with HRIS, Finance, Talent Acquisition, and EPD leadership to improve data integrity and operational decision-making.

Lead complex data analysis across Liftoff’s supply-side business, using optimized SQL on large-scale datasets and BI tools to build dashboards, reporting pipelines, and actionable insights. The role conducts root-cause analysis, evaluates experiments, translates technical developments into business impact, leads cross-functional initiatives, and mentors analysts. It partners with Engineering, Product, Data Science, Finance, Commercial teams, and executive leadership to influence roadmap and operational decisions.

Supports private-market asset data workflows by processing and reconciling data, monitoring exceptions, maintaining quality standards, analyzing trends, documenting operational logic, coordinating offshore teams, and partnering with Product, Data, and Engineering on process and product improvements.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Supports private-market document processing, data-quality reconciliation, exception triage, workflow management, and offshore team coordination. Serves as a subject-matter expert on private-market data, analyzes trends, documents operational logic, identifies process improvements, and collaborates with Product, Data, and Engineering teams on roadmap and systemic fixes. Provides operational summaries and data-quality reports to support client-facing teams.

Own product analytics for embedded business areas, leading experimentation, root-cause analysis, business-case development, KPI reporting, and strategic recommendations. Build dashboards and Looker explores, partner with engineering teams to improve data models and reliability, present insights to leadership, use AI tools to improve analytics efficiency, and mentor analysts. The role requires advanced SQL, Python, statistical experimentation expertise, and experience with consumer fintech or similar B2C data.

Analyze complex data to support emerging payments and AirKey initiatives. Build data solutions, self-service tools, dashboards, metrics, and visualizations; provide business insights; and support data quality, metadata, lineage, security, and access governance. Collaborate with business and technology teams while using Python, R, Spark, SQL, Snowflake, AWS, and data governance tools.

Analyzes and reconciles immigration and detainee movement data using the Inmate Information System. Verifies detainee statuses, investigates facility assignment and count discrepancies, corrects records, and prepares daily, weekly, monthly, and quarterly reports. Coordinates reporting with ICE, legal, municipal, and other designated agencies, performs SCOC data entry, communicates updates to supervisors, and supports emergency analytical tasks.

Build Confido’s analytics layer by creating dashboards, reports, metrics, and analytical tools for internal and customer users. Analyze large financial and operational datasets with advanced SQL, identify trends and inefficiencies, and translate findings into actionable recommendations. Partner with product, engineering, customers, and other stakeholders to improve data models, deliver analytical projects, and support decision-making across retail, finance, and operations.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.

Own client data onboarding by mapping source systems into a software platform, loading and validating messy files, troubleshooting live data issues, and documenting repeatable procedures. Explain technical findings to non-engineering teams, trace discrepancies to root causes, and collaborate with technical leaders on reusable checks, automation, and governance standards. Balance onboarding responsibilities with ongoing data troubleshooting.

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

Analyze multi-platform, multi-market media campaign data, connect ad delivery metrics with campaign KPIs, validate and transform datasets, run AWS and BigQuery queries, create visualizations, and provide insights supporting sales and client account performance.

Analyze marketplace and product performance using SQL, support experiments and advertising-effectiveness studies, build reusable datasets, QA metrics, and document analytics. Collaborate with analytics engineers, data scientists, product managers, engineers, and commercial teams while developing skills in statistics, causal inference, Python/R, and marketing science.

Conduct end-to-end data analysis, translate ambiguous business questions into actionable recommendations, and support decision-making across company functions. Build and maintain dbt models, tests, documentation, curated tables, semantic-layer metric definitions, and BI reporting. Partner with data engineering and stakeholders to ensure data quality, governance, and self-service access for people and AI agents. Maintain dashboards and identify opportunities across multiple business verticals.

Supports business operations by researching, validating, categorizing, and maintaining master data. Responsibilities include updating product information, verifying specifications, performing data quality checks, maintaining Excel documentation, and responding to business-user inquiries. The intern collaborates cross-functionally to ensure accurate and consistent data while following established processes.

Own analytics engineering and the data transformation layer by designing data models, warehouses, cubes, semantic layers, and governance frameworks. Improve data quality, observability, metadata, self-service analytics, dashboards, and reporting platforms. Analyze large datasets, optimize queries, conduct testing and code reviews, support modernization initiatives, and collaborate across teams to deliver trusted metrics and insights.

Conduct geospatial and molecular HIV data analysis using R, SQL, or Python; manage, merge, validate, and document datasets; support data governance, reporting, and dissemination; and develop or maintain Power BI dashboards. Collaborate with analysts, review data quality issues and error logs, document corrections, and provide project updates while supporting CDC public health surveillance initiatives.

Develop and maintain Tableau dashboards, data visualizations, analytics solutions, and reporting tools. Clean and transform data using Databricks, SQL, and Python; identify workflow automation opportunities; and partner with stakeholders to deliver analytics and AI use cases. The role also involves client presentations, requirements gathering, business development support, and federal government consulting.

Oversee compliance, data quality, documentation, referral closure, eligibility timeliness, billing readiness, and audit preparedness for Social Care Network activities. The analyst audits records, tracks performance metrics, identifies risks, maintains policies and procedures, supports corrective actions, and leads internal and external audit coordination. The role collaborates with navigators and leadership to ensure alignment with New York State 1115 Waiver, PHS, SOMOS, and program requirements.

The Finance Data Analyst manages finance ETL processes, reconciles enterprise data warehouse outputs, investigates discrepancies, and validates insurance financial data. Responsibilities include SQL-based analysis of premiums, commissions, taxes, fees, and payments; building automated controls and exception reports; supporting Finance reporting and close activities; documenting data processes; and partnering with Finance and data engineering teams to improve data quality and reliability.

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.

Develops dashboards, data models, reports, and analytical solutions that transform raw data into actionable business insights. Partners with stakeholders, provides technical guidance, documents architectures and processes, troubleshoots analytics solutions, and communicates findings to technical and non-technical audiences. Requires advanced Spotfire, SQL, business intelligence, and data analytics expertise, with knowledge of Databricks, Power BI, Python, R, Salesforce, and modern data architecture.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Analyze pricing, driver earnings, and market data to influence product roadmaps. Develop hypotheses, analytical frameworks, predictive and quantitative models, financial and business models, data pipelines, and analytical tools. Collaborate with product leads to build scalable pricing systems and processes, while using optimization, programming, and machine learning to support business decisions.