Top Data Analyst Jobs in NYC, NY

Develop KPI frameworks, track SLA performance, analyze operational data and alerts, and produce recurring reports for a federal and DoD-aligned mission environment. Validate and reconcile data across sources, support dashboard and engineering teams, identify trends and anomalies, and provide actionable insights and executive summaries. The role also maintains reporting standards, documents analytical processes, and supports operational and leadership decisions.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

Analyzes platform usage, client growth, query performance, infrastructure capacity, and cloud/AI costs. Builds scaling scenarios, monitors AWS and GCP utilization, identifies anomalies and waste, owns product analytics reporting, and partners with Engineering and Product on database scaling decisions. The role also documents optimization results, capacity thresholds, vendor utilization, and model assumptions while translating technical findings for business stakeholders.

Develop business intelligence and analytics solutions using financial, operational, RF, and video performance data. Build scalable data models, dashboards, reports, automation workflows, and ETL/ELT processes using Power BI, Tableau, DataMiner, and Qligent. Analyze trends and anomalies, monitor satellite and video delivery performance, translate business requirements into actionable insights, and collaborate with enterprise stakeholders in a fully remote consulting role.

Analyzes complex datasets to uncover business insights, develops dashboards and reports using SQL and visualization tools, and presents recommendations to stakeholders. Partners with engineering, operations, and other teams to solve business problems, prioritize strategy and projects, manage deliverables, and ensure data accuracy and timeliness.

The Data Governance Analyst will design and implement data governance practices, maintain metadata, and enhance data quality and compliance, collaborating with teams across the enterprise.

Own marketing analytics and measurement to improve acquisition, campaign performance, and marketing ROI. Lead multi-touch attribution, marketing mix modeling, A/B testing, incrementality studies, and KPI analysis. Partner with Marketing and Product to improve data quality, translate complex findings into recommendations, influence senior stakeholders, and coach peers on analytics practices.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

Build and manage Power BI dashboards and reports for fundraising performance, analyze large datasets and KPIs, identify trends, improve data workflows, and translate findings into clear recommendations. Partner with fundraising, marketing, analytics, and leadership teams to support data-driven decisions. The role requires advanced SQL, strong data visualization, fundraising or financial analytics experience, and a relevant bachelor’s degree.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Summer Analyst in Data & AI will design and build end-to-end data, analytics, and ML/AI solutions using cloud and modern tooling. Responsibilities include developing models and pipelines, running experiments tied to business KPIs, supporting data governance and compliance, creating dashboards, and collaborating in agile teams while receiving mentorship and training.

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.

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.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

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.

Analyze operational, payment, enrollment, survey, and field data to identify fraud risks and anomalies. Design and validate fraud-risk indicators, support investigations, improve data quality, and translate findings into actionable recommendations. Partner with Product, Data Engineering, and operational teams to develop fraud-detection tools and improve controls. Document reproducible, audit-ready analysis while communicating uncertainty and findings clearly to nontechnical stakeholders.

Analyze purchasing, payment, fraud prevention, and subscriber retention data to guide product and business decisions. Lead commerce experimentation, define metrics, validate randomization, build SQL analyses and data pipelines, and create Looker and Tableau dashboards. Partner with Product, Engineering, Data Science, and Business Operations teams to develop actionable recommendations, improve transactional data usability, and communicate findings through statistical analysis and executive presentations.

Lead AI solutions development in finance using statistical methods and machine learning. Mentor, implement models, ensure compliance, and collaborate for effective tool integration.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

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.

Senior Data Analyst translating business needs into technical data specifications, querying and transforming large datasets with SQL and Python, validating deliverables, and communicating insights to technical and non-technical stakeholders. The role supports commercial decisions, client deliverables, pre-sales, RFPs, reporting, and data quality initiatives while managing multiple concurrent requests.

Analyzes and corrects claims data errors, investigates root causes, evaluates business impact, and recommends long-term data quality improvements. The role manages claims corrections using business rules, resolves exceptions across systems, collaborates with claims administrators, programmers, vendors, and business teams, and produces ad hoc reports. Strong SQL skills and insurance claims knowledge are required; Snowflake experience is preferred.

Drives data collection, analysis, KPI reporting, dashboard development, forecasting, and executive presentations. Builds standardized reporting processes, improves data quality, investigates metric fluctuations, and translates business requirements into actionable insights. Collaborates with cross-functional teams, leadership, vendors, and partners to prioritize information needs, maintain data integrity, automate reporting, and communicate findings effectively.

Analyze Workday and enterprise data using SQL and Python; build dashboards, reports, data pipelines, and AI workflows for summarization, classification, and information extraction. Partner with business teams to define reporting needs, improve processes through generative AI and automation, connect AI applications to enterprise systems and APIs, validate data quality, and document technical solutions.

Lead development and operationalization of enterprise data risk frameworks, KRIs/KPIs, and risk registers. Produce dashboards and reporting, track remediation, partner with data, technology, risk, and compliance teams, and support data protection, governance, and adoption activities across cloud data environments.