Top Artificial Intelligence Data Science Jobs in New York City, NY

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate insights; and drive data-informed decisions with cross-functional stakeholders. The role requires independently structuring ambiguous problems, using SQL or Python, communicating findings clearly, and delivering measurable business impact.

Lead data science and analytics initiatives supporting product, engineering, leadership, and insurance clients. Analyze claims and product data, design experiments, generate hypotheses, measure ROI, build dashboards and reproducible analytics, and communicate actionable recommendations. Mentor junior analysts, conduct client-facing analyses, collaborate with ML teams, investigate data issues, and shape product strategy through sophisticated statistical modeling and exploratory analysis.

Analyze product and user data to guide product strategy, operations, and roadmaps. Design experiments, apply causal inference, investigate anomalies, define metrics, build statistical models and simulations, and establish scalable analytics practices. Present actionable insights to technical and business stakeholders while supporting data-informed decision-making for AI products.

As a Data Scientist, you will advance applied ML capabilities for healthcare, develop LLM-based chart abstraction techniques, and enhance data science best practices.

Build and own the analytics pipeline and semantic layer, define canonical product and business metrics, evaluate AI/agent performance, support pricing and profitability analysis, design dashboards and quality checks, translate ambiguous questions into analyses, and hire/scale the data team.

Own Data, Cloud & AI coverage using a proprietary dataset to produce forward-looking, data-driven research. Analyze trends across AI/ML operations, databases, data integration, governance and cloud infrastructure; produce client-facing insights, thought leadership, and collaborate with product and engineering to improve research methodology and platform fidelity.

Quantitative Researchers develop predictive models, apply statistical methodologies to financial data, and design frameworks for risk and returns analysis.

The Senior Data Scientist will lead analytical projects, develop bespoke solutions for clients, manage teams, and present findings to drive client satisfaction and retention.

Lead end-to-end data science engagements combining statistical modeling, machine learning, large-scale data transformation, and generative AI. Build agentic LLM applications, present analytical solutions to C-level stakeholders, lead workstreams, mentor junior data scientists, and collaborate with delivery and account teams. Develop reusable documentation and code libraries while contributing to internal research and education.

Lead marketing measurement and effectiveness programs using marketing mix modeling, incrementality testing, attribution, causal inference, experimentation, and optimization. Own statistical methodology, production deployment, GenAI applications, client relationships, executive communication, team development, and account growth. Translate models into budget and media decisions, build reusable measurement accelerators, uphold scientific rigor, and remain hands-on with technical problem-solving, MLOps, cloud industrialization, and model review.