Top Data Analyst Jobs in NYC, NY

Support AP/AR, reconciliations, transaction processing, month-end close, financial reporting, and discrepancy analysis. Build data pipelines and automated workflows using APIs, integrations, Python, SQL, and spreadsheets. Help connect accounting and operational systems, validate financial data, and improve finance processes while gaining experience with scalable financial infrastructure.

Analyze stakeholder and project requirements, translate them into functional features, partner with Product, Engineering, and QA, define acceptance criteria and test cases, identify bugs, support resolution, perform functional testing, and provide product sign-off. The role also involves documenting use cases, communicating decisions, and developing data-product solutions using SQL and the company’s data stack.

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

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

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.

Analyzes structured and unstructured datasets, identifies data quality issues, builds SQL database models and ETL processes, and creates Tableau visualizations. Translates technical findings into client-ready reports and presentations, supports financial and operational impact assessments, documents methodologies, and coordinates project activities with clients and internal teams.

Data Analyst Intern supporting Dow Jones data management projects through reporting, dashboard development, quantitative analysis, data exploration, and stakeholder communication. Responsibilities include delivering customer-facing reports, interpreting trends, building dashboards with visualization tools, and supporting data pipelines, models, algorithms, and visualizations. Candidates must be undergraduate students with quantitative coursework, SQL or Python knowledge, strong Excel skills, and an analytical, curious mindset.

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.

Leads fraud analytics strategy for digital payments, defining risk frameworks, fraud metrics, and analytical models. Partners with Product, Engineering, and Risk Operations to turn insights into scalable fraud mitigation solutions. Manages external data sources, defines requirements for production data pipelines, and establishes best practices for risk measurement and modeling. Serves as a senior thought leader influencing cross-functional stakeholders and executive decision-makers.

Lead business analysis for CFO, Treasury, regulatory reporting, risk, data, and technology initiatives. Translate complex business and regulatory needs into requirements, data mappings, user stories, acceptance criteria, and test scenarios. Analyze financial data with SQL, assess impacts across systems and reporting, resolve data-quality issues, and coordinate UAT through implementation. The role requires strong financial-services knowledge, Agile delivery experience, stakeholder management, and the ability to drive controlled outcomes across complex environments.

The HR Data Analyst develops and maintains workforce dashboards, KPIs, reports, and automated analytics solutions. They analyze employee lifecycle, engagement, retention, talent, learning, rewards, and HR operations data to identify trends and provide recommendations. The role partners with HR and business leaders, presents insights, ensures data quality and compliance, and improves reporting processes through governance, validation, automation, and data modeling.

Analyzes claims data to identify trends, patterns, risks, and business opportunities. Retrieves, validates, and prepares data from multiple databases; creates reports, dashboards, visualizations, spreadsheets, and presentations; supports forecasting and reporting needs; collaborates with claims, underwriting, product, IT, and leadership teams; and communicates recommendations for business decisions and process improvements.

Build Python and SQL data pipelines, maintain data integrity, automate dashboards and reporting, and deliver actionable analytics. Develop AI- and LLM-assisted workflows for data enrichment, classification, summarization, and process automation. Support leadership decision-making, sales, customer success, and internal efficiency while communicating insights to nontechnical stakeholders. Evaluate, document, and monitor AI solutions for accuracy, cost, risk, and auditability.

Analyze operational data, build and maintain Power BI dashboards, validate data quality, investigate trends and discrepancies, document reporting definitions, and communicate findings to business stakeholders. Partner with IT, data engineering, and analytics teams to resolve data issues and support reliable reporting. Use SQL, Power Query, DAX, Excel, and AI-enabled analytics tools to transform data and inform process improvements.

Supports energy and sustainability analytics for data center clients by cleaning, validating, and analyzing datasets; developing Power BI or Tableau dashboards, dataflows, and reports; documenting methodologies; performing quality checks; and delivering accurate outputs across concurrent projects. Collaborates with energy and sustainability teams, learns internal analytics platforms, and identifies opportunities to improve reporting, automation, and workflows.

Analyzes operational and financial data to identify trends, risks, and opportunities; develops forecasts, regression models, scenarios, dashboards, visualizations, and recommendations for business decision-making. Partners with business leaders to define requirements, communicates insights, and supports data governance, quality, stewardship, modeling, and privacy initiatives.

Analyzes marketing data to guide investment decisions, improve campaign performance, segment customers, support A/B testing, and identify conversion opportunities. Builds dashboards and reports, maintains metric definitions and data quality standards, investigates anomalies, and communicates actionable insights to sales, marketing, and global operations partners.

Analyze case, client, and financial data to build Power BI dashboards, executive and client reporting, recurring Excel deliverables, SQL analyses, and lightweight automations. The role investigates discrepancies, supports ad hoc business questions, documents metric definitions, and partners with operations, sales, finance, and leadership to improve reporting and reduce manual work.

Owns the CX Operations data foundation in Snowflake by designing architecture, governance, data quality standards, and reusable dbt models. Leads complex analyses, dashboards, scenario planning, and executive communication while mentoring analysts and partnering with engineering and strategy teams. Supports AI enablement by creating trusted data models, evaluation standards, and agent performance tracking.

Supports a defense aviation modernization program by integrating and analyzing complex program data across cost, schedule, risk, logistics, testing, configuration management, and cybersecurity. Develops dashboards and executive reports, performs KPI and performance analysis, supports program reviews and aircraft integration efforts, tracks test results and corrective actions, and automates reporting processes. Requires extensive DoD or aerospace experience, aircraft modernization expertise, and an active Secret clearance.

Analyzes operational, engineering, logistics, reliability, maintenance, training, supply chain, and program data for a NATO SATCOM support program. Develops executive dashboards, KPIs, scorecards, predictive reports, trend analyses, and risk assessments. Maintains product support databases, validates data integrity, supports reliability and sustainment analyses, and reports on readiness, quality, cost, schedule, and lifecycle performance. Presents actionable recommendations to technical and executive stakeholders.

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.

Loads, queries, validates, and analyzes data; refreshes databases; prepares client reports; identifies automation opportunities; supports UAT, system implementations, and quality assurance; and collaborates with cross-functional teams. The role requires database management, SQL, Oracle, Unix, Python, Power BI, data modeling, and relational database expertise, with opportunities to use scheduling and master data management tools.

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.