Top Data & Analytics Jobs in NYC, NY

Build scalable customer experience data systems, pipelines, dashboards, metrics, and reporting frameworks. Analyze customer interactions and operational data to identify performance drivers, root causes, and improvement opportunities. Develop AI and LLM-powered quality assurance and feedback workflows, maintain data governance, and ensure analytics platform reliability. Partner with Customer Success, Support, Product, Engineering, and Data teams to deliver actionable insights and executive reporting. Manage NPS outreach and communicate recommendations to leadership.

Leads Data Engineering, Data Governance, and BI/Analytics teams while owning enterprise data platform architecture, pipelines, governance, warehouse or lakehouse design, BI strategy, and data quality. Serves as the technical bridge between data teams and business stakeholders, manages the platform roadmap, and oversees governed data integration for Glean AI search and agent tools. This hands-on director role combines architecture, engineering, people leadership, strategic planning, and stakeholder partnership.

Owns the design, development, operation, and governance of data pipelines and integration patterns supporting Medical Affairs AI products. Builds APIs and ETL/ELT solutions connecting enterprise systems to analytics platforms, RAG pipelines, vector databases, and GraphRAG applications. Ensures data quality, privacy, lineage, compliance, and protection of sensitive information. Partners with architecture, engineering, product, and business stakeholders to deliver reusable, production-grade data integrations.

Own CX data infrastructure, including pipelines, data models, governance, monitoring systems, and Streamlit dashboards. Apply advanced statistics and AI-assisted anomaly detection to identify customer experience opportunities and performance issues. Partner with CX leaders, data science, engineering, and Salesforce teams to define metrics, answer causal questions, and guide operational decisions. Establish data quality standards, validate AI-generated outputs, communicate insights clearly, and mentor data practitioners.

Support GTM compensation lifecycle, quota/target setting, and performance analytics. Reconcile commission data across systems, build reporting, model scenarios, and deliver decision-ready insights to RevOps and GTM leaders.

Design and scale lakehouse architecture, including Bronze, Silver, and Gold data layers. Build reliable streaming and batch pipelines with Kafka, Spark, and Airflow; manage Iceberg, Delta, and Hudi table formats; optimize Trino, Starburst, and Databricks queries; and improve platform reliability, data quality, and performance. Collaborate with data scientists, analysts, and product teams to deliver scalable data platform solutions.

Designs and maintains dashboards, reports, and visualizations; validates data quality and reporting logic; translates complex analysis into actionable recommendations; partners with data teams and stakeholders; improves reporting scalability, self-service analytics, and responsible AI usage. Presents findings to technical and non-technical audiences while supporting strategic and operational decision-making.

Analyze payment fraud data using SQL and dashboards, identify anomalous behavior and risk trends, evaluate fraud controls, and recommend improvements. Present findings to leadership and collaborate with Product, Data Science, Engineering, Customer Experience, and Risk Analytics teams. The intern will also document risk processes and responsibly use generative AI to improve workflow efficiency and quality.

Leads commercial analytics strategy and client storytelling for pharma and agency partners. Translates campaign measurement, media mix, healthcare datasets, and cross-brand trends into actionable recommendations that support sales, renewals, product positioning, and client outcomes. Serves as a senior thought partner and public-facing industry voice, presenting data-driven insights to executive stakeholders and conferences while collaborating with Sales, Marketing, Product, and Campaign Measurement teams.

Own January’s trusted analytics layer by designing a dbt-driven semantic layer in Snowflake, standardizing metrics and data contracts, improving client reporting, expanding data capture, and managing analytics costs. The role enables trustworthy self-service across dashboards, chatbots, and future AI agents while partnering with Data Engineering, Analytics, Borrower Support, and Client Acquisition.