Top Tech Jobs & Startup Jobs in NYC, NY

The Manager of Marketing Mix Modeling will oversee MMM builds and integration, ensuring quality and strategic actionability of model outputs, guiding cross-functional teams in data-informed decisions.

Lead strategy, execution, and optimization across video, audio, and programmatic display channels; manage client relationships and budgets; align channel efforts to enterprise measurement (EMR); oversee DSP bidding, trafficking, and inventory; train and develop team members; drive cross-functional integration and testing to unlock profitable, full-funnel growth.

The Data & Software Engineer will develop, test, and deploy software solutions, automate processes, and collaborate with stakeholders to enhance data performance and stability.

Lead the design, build, and ownership of production AI workflow and integration infrastructure enabling non-engineers to configure multi-step LLM-driven automations. Architect connectors, orchestration, security, CI/CD, monitoring, and bidirectional write-back while partnering with stakeholders and enforcing governance and compliance.

The Paid Search Manager will manage client relationships, lead a team, drive paid search strategies, and oversee performance media management for enterprise-level accounts.

The Engineering Manager leads a cross-functional team to develop and optimize scalable software solutions, mentor team members, and ensure adherence to engineering practices and agile methodologies while collaborating with stakeholders.

The Manager of National Video Investment leads national linear television media buying, manages relationships with media partners, negotiates buys, provides insights, and supports cross-functional marketing strategies.

The Data & Software Engineer will design, develop, and maintain scalable software and data solutions, ensuring alignment with business needs while collaborating with cross-functional teams.

The role involves leading the design and delivery of an AI Analytics Platform, focusing on building RAG systems, integrating enterprise systems, and mentoring engineers.

Build and maintain integrations and multi-step automated workflows between the enterprise AI platform and operational tools. Implement and sustain write-back logic, troubleshoot integration issues, ensure production reliability and security, support non-technical practitioners, participate in reviews, and contribute to monitoring, documentation, and training.