Top AI & Machine Learning Jobs

Build and deliver reliable statistical and machine learning models, analyses, datasets, and scoring workflows for business and intelligence initiatives. Responsibilities include data preparation and validation, modeling, evaluation, documentation, monitoring, batch scoring, API integration, and stakeholder communication. The role requires independently owning defined deliverables, translating business questions into analytical solutions, and applying AI-assisted development while maintaining statistical rigor, operational discipline, and trustworthiness.

Lead the product strategy and architecture for Zeta’s agentic AI platform, including LLM agent orchestration, context graphs, real-time context streaming, telemetry, observability, evaluation suites, model workbench capabilities, and MCP tool governance. Align Product, Engineering, Data Science, Design, Security, and business teams around platform standards and priorities. Prototype solutions, troubleshoot technical issues, and establish feedback loops for continuous improvement of agent performance and user outcomes.

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.

Develop and deploy machine learning models powering real-time bidding, advertising decisions, reporting, and customer predictions. Solve propensity modeling, bidding strategy, A/B testing, CLTV, and churn prediction problems at large scale. Build enterprise-grade data and machine learning platforms, write modular production code, collaborate with engineers, and own projects from concept through implementation.

Build and deploy production-grade ML/LLM solutions for ad targeting, ranking, pacing, personalization, and creative intelligence. Design low-latency ML lifecycles, operate services at scale, integrate agentic LLM workflows, optimize inference, monitor model performance, and mentor engineers.

The Senior Manager, Data Science & Analytics will lead the analytics strategy for client engagement, focusing on data-driven insights and marketing performance to assist in customer acquisition efforts.