Top Senior Data Analyst Jobs in NYC, NY

The Senior Data Analyst will enhance marketing measurement programs, conduct in-depth analyses, develop data models, and mentor peers, focusing on actionable insights.

Lead analytics for Brigit's Line of Credit product: define core metrics, forecast revenue and costs, design experiments, optimize underwriting and collections, evaluate and monitor predictive models, build dashboards, and deliver ad-hoc analyses to influence product, finance, and leadership decisions.

The Senior Data Analyst for Payments will analyze and optimize payment processes, collaborate with cross-functional teams, and ensure regulatory compliance to improve financial operations.

The Senior Data Analyst will own data models and drive analytical initiatives, ensuring data quality and reliability while providing insights to stakeholders. Responsibilities include managing dashboards and supporting the team with analytics.

The Senior Data Analyst will manage financial ROI models and product analytics, working with cross-functional teams to enhance healthcare outcomes through data-driven insights.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

The Senior Data Analyst will partner with clinics to analyze financial performance and operational efficiency, design reports, and communicate insights effectively.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Senior Data Analyst partners with Product, Marketing, Finance, and leadership to deliver data-driven insights. Responsibilities include SQL/Python analysis, predictive modeling, forecasting, automating reporting, building dashboards and datasets in Snowflake/Looker, running A/B tests in LaunchDarkly, and communicating findings to influence product and company strategy.

Senior Data Analyst partnering with product, engineering, sales, and operations to define analytics roadmaps, craft complex SQL analyses, build Tableau dashboards, evolve the data warehouse with Data Engineering, maintain data cataloguing and governance, ensure analytics SLAs, and mentor junior analysts.

The Senior Data Analyst will build dashboards, ensure metric quality, and provide insights to support decision-making across teams. Responsibilities include data analysis, problem framing, and collaborating with stakeholders to improve data utilization.

The Senior Revenue Operations Analyst will ensure data quality across systems, integrate third-party data into CRM, define quality metrics, and collaborate cross-functionally to improve data processes.

Plan and execute IT advisory, assessment and audit projects using GRC practices. Perform cybersecurity audits, risk assessments, controls reviews, and HIPAA compliance assessments. Document and present findings, maintain work papers, liaise with stakeholders and external auditors, and recommend risk mitigation and performance improvements.

Maintain data dictionary and lineage; design logical and physical data models; map attributes to source documents; validate data quality; support data governance and compliance; collaborate with BI and analysts to enable reporting and Tableau dashboards.

Lead complex analyses to optimize viewer engagement, content performance, and operations across 1P/3P/FAST ecosystems. Build scalable dashboards, own WBR/MBR reporting, design and evaluate A/B tests, validate data quality, automate reporting, support forecasting, and translate quantitative findings into executive recommendations.

As a Senior Product Data Analyst, you will analyze payment data, define metrics, design experiments, and provide insights to enhance product decisions.

The Senior Data Analyst will develop and maintain ETL pipelines, conduct data analysis on large datasets, and design interactive dashboards to support data-driven decisions.

Lead healthcare analytics work using claims and product data: calculate PMPM and utilization metrics, validate data refreshes, design data models and algorithms, build Looker dashboards, and document/train stakeholders. Serve as a healthcare data SME collaborating with clinical, operations, and finance teams.

The Senior Data Analyst will manage data quality and governance for regulatory compliance, build data marts, and optimize data models for performance and scalability. This role includes supporting regulatory exams, establishing monitoring for data feeds, and translating regulatory requirements into data flows.

Lead collection, organization, and analysis of multi-source data for influencer marketing campaigns; build and maintain dashboards; identify optimization opportunities; provide cross-functional data-driven recommendations; mentor junior analysts; stay current on data analysis and influencer marketing best practices.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

As a Senior Data Analyst for Fraud Strategy & Operations, you will analyze data to identify fraud trends, build predictive models, design fraud prevention rules, and collaborate with cross-functional teams to enhance fraud detection capabilities.

The Senior Data Analyst will collaborate across teams to provide insights, build analytics databases, create dashboards, and automate reporting solutions. They will analyze data trends and partner with IT and product teams to enhance data models.

The Data Governance Analyst curates metadata, implements governance workflows, supports data quality checks, and drives governance tool adoption to enhance data strategy.

Design, implement, and optimize data quality management solutions and governance workflows. Collaborate with data product managers, business SMEs, and engineering to improve data quality, discoverability, lineage, and compliance. Support tool implementation (Anomalo, metadata tools), run data profiling/cleansing, document standards, enable users through training, and participate in Agile delivery and backlog prioritization.