Top Data & Analytics Jobs in NYC, NY

As a PhD intern, you will develop and test trading strategies, perform statistical analysis, and collaborate with senior researchers.

Conduct quantitative research for automated trading strategies by developing mathematical models, translating algorithms into code, backtesting trading signals, analyzing unconventional data, and refining monetization systems. Collaborate with senior researchers during an 11-week post-doctoral internship while applying advanced probability, statistics, machine learning, and time-series techniques to financial markets.

Own end-to-end analytics engineering for AI and developer-experience telemetry, including instrumentation, production pipelines, governed metrics, monitoring, executive dashboards, and analysis. Define and validate new measures of AI productivity and ROI, communicate findings to senior stakeholders, and recommend improvements to tooling, processes, and investment. Collaborate with data engineering, applied AI, and data science teams while using AI coding agents to build and maintain pipelines and reporting.

Lead a distributed team of five Data Integration Engineers supporting client integrations. Oversee complex data flows, endpoint design, data quality, validation, and integration escalations. Establish priorities across client commitments and business goals, improve onboarding speed and quality, and develop shared tools, processes, automation, and AI-driven validation workflows. Collaborate with Operations, Sales, Product, Development, and Data Science teams while serving as a technical and strategic advocate for clients.

Analyzes business challenges and opportunities for Capital One Shopping, developing strategic recommendations, product and pricing models, credit risk models, marketing insights, and monitoring plans. Leads cross-functional initiatives with IT, Sales, Operations, and Finance to improve growth, profitability, customer experiences, and credit performance. Requires strong quantitative analysis, communication, business judgment, and execution skills.

Develop and deploy analytical and AI-enabled tools integrated with the Aladdin platform to support portfolio construction, investment research, relative value analysis, risk budgeting, due diligence, and portfolio monitoring. Partner with portfolio managers and engineering teams to identify opportunities, prototype solutions, manage delivery, and productionize scalable applications. Communicate insights clearly while applying knowledge of financial markets, asset classes, Python, SQL, and modern technology stacks.

Own supervisory data management and governance as a subject matter expert. Define data quality rules, metrics, monitoring, issue remediation, taxonomies, metadata, and cataloging practices. Partner with business, IT, and platform teams to improve data reliability, accessibility, lifecycle management, and future AI readiness. Translate business needs into technical requirements, facilitate adoption of governance practices, and communicate recommendations to technical and executive audiences.

Designs and develops scalable data architectures, pipelines, data warehouses, and analytics solutions across on-premise, cloud, and hybrid environments. Performs data wrangling and discovery, collaborates on business intelligence initiatives, mentors data engineers, contributes to technical capability development, and supports project planning and estimation.

Drive AI data readiness across Asset Management by strengthening metadata, documentation, data quality, access controls, governance, and ontologies. Partner with business, data, product, and technology stakeholders to translate AI use cases into actionable requirements and deliverables. Coordinate dependencies, risks, issues, and delivery plans across workstreams while analyzing data to identify trends and inform prioritization. Promote data operating model improvements and use Jira and Confluence to manage agile execution and stakeholder transparency.

Lead quantitative and qualitative market research across customer panels, brand tracking, thought leadership, and advertising concept testing. Manage research vendors, survey platforms, participant recruitment, data quality, and panel operations. Synthesize findings into executive-ready recommendations and data stories for marketing, product, and communications teams. Build reusable research frameworks, improve ResearchOps workflows, support data governance, and provide light mentorship to junior team members.

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.