Top AI & Machine Learning Jobs in New York City, NY

The role involves leveraging technologies like Python and AWS to develop statistical and machine learning models, translating complex data insights into business goals, and working with a cross-functional team.

Lead a team of data scientists to develop AI/ML solutions, leveraging advanced technologies for customer interactions and product innovations. Build and implement NLP models for large-scale applications while collaborating with cross-functional teams.

Design, build, validate, and deploy machine learning models across the credit card lifecycle. Partner with cross-functional teams, analyze large numeric and textual datasets using Python, Spark, H2O and cloud platforms, and translate technical insights into business impact for card products.

Lead product management for Capital Ones Enterprise AI/ML platform, building intelligence capabilities and tools for data scientists and ML engineers. Drive roadmap, cross-functional execution with engineering, risk, security, and business partners, ensure governance, resiliency, and cost controls, and deliver scalable, user-centered platform experiences.

Lead and deliver card fraud detection solutions: design, train, validate, and deploy machine learning models at scale using big-data tools. Partner with engineers and product managers, translate technical work to business impact, and coach team members while leveraging cloud and open-source technologies.

As Director of Data Science, you'll lead a data science team to build generative AI solutions, leveraging machine learning and large-scale data analysis to enhance customer experience and drive business decisions.

Lead product management for Capital One's Enterprise AI/ML platform, building capabilities for data scientists, ML engineers, and developers. Drive platform strategy, deliver resilient and governed AI solutions, collaborate with engineering, risk, security, and business teams, and translate user needs into scalable, operational products.

Owner of product features for Card Intelligence ML initiatives; collaborate with data scientists, engineers, and stakeholders to define roadmaps, break down epics into MVPs, prioritize features, and accelerate model-to-market delivery for fraud prevention.

Lead development of next-generation entity resolution solutions using transformers, graph ML, deep learning, and big-data tooling. Partner with engineers and product to design, train, evaluate, validate, and deploy ML models at scale; leverage Agentic AI workflows; translate technical work into business impact across enterprise use cases.

Lead development and deployment of machine learning models using bureau and large-scale numeric/text data. Partner with engineers and product to build, validate, and implement data products, extract insights, and align technical work to business goals while mentoring and influencing stakeholders.