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

Summer intern assisting with IT solution design and implementation, supporting cybersecurity initiatives through security protocol analysis, and collaborating with data science teams to analyze data and generate actionable insights. The role offers hands-on experience, mentorship, and professional development within Honeywell Aerospace. Candidates must remain enrolled in a relevant degree program, maintain at least a 3.0 GPA, and meet U.S. person requirements.

Leads client-facing data science and analytics initiatives, translating complex marketing and media data into actionable business narratives. Develops measurement strategies, including test/holdout incrementality, informs acquisition and retention decisions, scales analytics best practices, and manages analyst teams. Partners with Sales, Client Services, Operations, and other stakeholders while supporting predictive and adaptive AI/ML solutions. The role requires strong client communication, strategic leadership, analytics expertise, and proficiency with Python, SQL, Tableau, and related tools.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

Evaluate and validate machine learning outputs against financial theory, client objectives, and market dynamics. Translate research signals into investment strategies, portfolio construction, and testable modeling specifications. Design and scale quantitative models in Python and Java, develop financial validation frameworks, and collaborate with ML researchers and technical teams to integrate research into production. Communicate quantitative insights clearly across technical and business stakeholders.

Build and deploy pricing, underwriting, and risk-scoring models for commercial property and general liability insurance. Use bind, quote, loss, and exposure data to identify profitable segments, predict carrier pricing, improve underwriting guidelines, and monitor model performance. Partner with program leadership to translate model outputs into actionable underwriting decisions and recalibrate models as the business grows.

Develop machine learning, statistical, graph-based, and entity-resolution algorithms for large-scale identity verification and deceased monitoring. Build Spark/PySpark and AWS data pipelines, engineer features, analyze data quality, conduct experiments, and support model evaluation. Write Python/R and SQL for extraction and validation, investigate compliance data, create dashboards, and communicate findings to cross-functional teams.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations decisions. The role requires independent data work, strong analytical and communication skills, first-principles problem solving, and ownership of ambiguous initiatives through measurable business impact.