Top Tech Jobs & Startup Jobs in NYC, NY

Develop, implement, govern, and integrate enterprise ontologies and data models. Harmonize linked data, establish semantic and data-standardization guidelines, support knowledge organization and machine-learning integrations, and advocate semantic technology across Finance and Enterprise teams. Use W3C ontology standards and specialized tools to test, troubleshoot, and maintain models while collaborating with Technology, Product, and Machine Learning stakeholders.

Leads enterprise ontology and data-modeling strategy, governance, integration, standardization, and roadmap development. Manages teams creating semantic models, taxonomies, linked data, and reusable capabilities while partnering with technology, machine learning, and business stakeholders. Advocates W3C standards, supports knowledge organization workshops, establishes modeling guidelines, monitors industry trends, and mentors team members. Requires expertise in metadata, ontologies, linked data tools, graph technologies, SQL or SPARQL, and semantic standards.

Develops and governs enterprise ontologies, semantic models, and data standards. Partners with Finance, Technology, Product, and Machine Learning teams to integrate semantic technologies, harmonize linked data, improve data discoverability, and support product development. Responsibilities include applying W3C standards, managing ontology tools, testing models, advocating data standardization, monitoring industry developments, and overseeing related projects.

Lead development and deployment of machine learning models across the credit card lifecycle. Partner with cross-functional teams to build data-driven products, analyze large numeric and textual datasets, validate and implement models, and translate technical insights into business impact.

Leads product managers and data analysts delivering reusable risk data products for Enterprise Risk. Responsibilities include customer discovery, product strategy, prioritization, translating business epics into features and user stories, writing acceptance criteria, collaborating with engineering, troubleshooting data issues, overseeing releases, and using data analysis to guide product improvements.

Leads product strategy, delivery, operational accountability, and transformation for a major financial business unit. The role develops a technology- and AI-enabled operating model, manages critical processes and risks, drives change across people, process, and technology, and partners with product, technology, business, risk, audit, and regulatory stakeholders.

Lead product management and quality governance for Capital One’s Global Payments Network. Drive scalable end-to-end testing frameworks, environment strategies, data governance, and reliable payment experiences across authorizations, settlement, disputes, digital, pricing, risk, and go-to-market. Partner with Product, Technology, Operations, and other cross-functional leaders to improve customer journeys, institutionalize quality processes, ensure compliance, and deliver strategic, user-centered payment solutions.

As a Director, Data Scientist - Generative AI Systems, you will lead a team to develop AI products using NLP and generative AI technologies, partnering with cross-functional teams. Your role involves leveraging open-source programming and machine learning to convert customer data into actionable insights and enhance customer interactions with financial services.

Analyze payment, lending, marketing, and credit-risk data to identify business opportunities, build strategic recommendations, develop and monitor statistical models, and support product and pricing decisions. Partner with IT, Sales, Operations, Finance, and other teams to implement solutions, improve performance, and drive profitability. The role requires strong quantitative reasoning, business judgment, communication, leadership, and execution skills in a fast-paced environment.

Leads data analytics and business intelligence strategy, mining large datasets, building and validating models, improving processes and reporting, evaluating products and initiatives, and consulting on data systems. Manages and mentors junior analysts, collaborates across business units, and oversees projects from inception through completion. The role requires advanced analytical, programming, communication, leadership, and problem-solving skills.