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

Leads payer healthcare data science and operations consulting initiatives, using business analytics to improve payer processes and performance. Manages teams, client relationships, project resources, strategic planning, process optimization, quality standards, and operational transformation. Coaches junior staff, promotes innovative technologies, and identifies opportunities to enhance operational excellence and business outcomes.

Leads teams designing and deploying scalable AI and machine learning solutions. Responsibilities include data wrangling, software development, data infrastructure and pipeline management, model training, complex analysis, stakeholder collaboration, project execution, and mentoring. The role uses Python, C++, TensorFlow, and Scikit-Learn to transform data into business insights and drive innovation.

Analyzes complex data sets, develops Python-based data solutions and pipelines, and applies advanced analytics to support client strategy and business performance. Designs dashboards and visualizations, collaborates with cross-functional teams, manages stakeholders, improves data quality, and builds client relationships. The role also involves solving complex business challenges, identifying industry trends, and delivering high-quality work within PwC’s Risk & Regulatory practice.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Leads the development and implementation of conversational and agentic AI solutions for contact centers and other user interaction platforms. Manages multidisciplinary teams, translates client requirements into technical specifications, oversees UI development and human-centered design, conducts usability testing, and builds client relationships. Coaches junior staff, identifies innovation opportunities, and ensures successful project delivery aligned with client strategies and quality standards.

Leads AI modeling and data analytics strategies for AML and sanctions clients in banking and capital markets. Oversees multiple projects, develops strategic solutions, supports business development, maintains executive client relationships, and mentors teams. Responsibilities include improving data quality and architecture, validating analytics integrity and compliance, promoting AI-human collaboration, driving thought leadership, and converting market opportunities into business outcomes.

Leads AI and data-driven solutions for AML and sanctions clients in banking and capital markets. Responsibilities include developing AI solutions with Python, managing data architecture and pipelines, overseeing analytics and visualization deployments, guiding advanced analytics teams, engaging stakeholders, validating client outcomes, improving processes, and coaching diverse teams through complex situations.

Leads AI technology integration and deployment within the tax practice. Oversees data infrastructure, pipelines, modeling, quality validation, and multi-source integration. Develops Python-based analytics solutions using machine learning and natural language processing, conducts rapid experimentation, and drives data-informed innovation. Coaches and develops high-performing teams while collaborating with stakeholders and advising on strategic initiatives.

Design, build, and deploy scalable AI and ML solutions by wrangling and integrating data, implementing models (Python/Java, TensorFlow, Scikit-Learn), developing data pipelines and NLP applications, collaborating with clients, and mentoring junior team members to drive business insights and regulatory risk solutions.