Top Data & Analytics Jobs in NYC, NY

Analyzes advertising revenue, inventory utilization, sell-through rates, pricing, and business trends. Maintains Excel and Power BI reports and dashboards, organizes data from multiple sources, investigates discrepancies, and creates clear visualizations. Supports process automation using Power Query, Excel data models, and Access. Collaborates with analytical leads and cross-functional partners to communicate findings, improve reporting accuracy, and support business decisions.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

Own Confido’s end-to-end data function, including ingestion, warehouse architecture, pipelines, modeling, reporting, quality, governance, and privacy. Build and lead the data organization, establish its roadmap and technical standards, partner with cross-functional leaders, hire and develop the team, and remain hands-on with SQL, architecture, and code reviews while the organization grows.

Develop sophisticated investment and trading models using statistical techniques, machine learning, and real-world datasets. Conduct end-to-end quantitative research, test investment hypotheses, collaborate with engineers, analyze market behavior, and communicate complex findings. Participate in academic seminars, reading groups, and industry conferences focused on statistics, machine learning, and data science.

Lead quantitative consumer research on dating, identity, and connection, designing engaging surveys, analyzing emerging findings, and translating data into compelling stories for Communications and Product Marketing. Manage global and cross-cultural research initiatives, including reports, market stories, and product marketing studies. Partner strategically with marketing teams, develop research roadmaps, experiment with quantitative storytelling methods, and direct external research agencies.

Build and maintain finance data models, automated pipelines, dashboards, and reports for planning, forecasting, close, and executive reporting. Govern finance metrics, reconcile data to source systems and the general ledger, resolve data quality issues, and collaborate with FP&A, Accounting, and Data Engineering. Apply BI best practices such as dimensional modeling, documentation, testing, version control, and data governance while translating finance needs into scalable data solutions.

Build and operate production data pipelines, models, and data products supporting finance, accounting, treasury, compliance, and regulatory reporting. Partner cross-functionally to define requirements, model on-chain and internal data, and ensure data reliability through reconciliation, quality checks, monitoring, and alerting. Use SQL, Python, cloud data warehouse, Airflow, dbt, and AI tooling. Mentor engineers, review technical work, document systems, and communicate data concepts to technical and non-technical audiences.

Analyze revenue performance, forecasting, business drivers, and market trends to support planning and commercial growth decisions. Partner with Sales, Finance, Business Intelligence, and other stakeholders to identify risks, opportunities, and actionable insights. Develop segmentation, opportunity-sizing, prioritization analyses, and investment business cases. Improve recurring reporting and planning processes through automation and scalable tools, translating complex data into clear recommendations for senior leadership.

Leads quantitative and qualitative Medicaid policy research from project scoping through dissemination. Oversees data acquisition and analysis, monitors state and federal policy changes, develops briefs and presentations, conducts stakeholder interviews, supervises research staff, manages external collaborators, and translates findings into actionable recommendations for policymakers, providers, advocates, and the public.

Conduct quantitative research for proprietary trading strategies by analyzing high-frequency market data, developing statistical and machine-learning models, building simulations and backtesting tools, and evaluating model performance. Collaborate with traders and developers to validate algorithms, improve pricing and execution, assess production readiness, prioritize research initiatives, and integrate validated models into low-latency trading systems. Mentor graduate researchers and interns.