Top Tech Jobs & Startup Jobs in NYC, NY

Own marketing outcomes for customer pilots, from scoping use cases through audience activation, campaign measurement, diagnosis, and expansion. Partner with account executives, founders, and forward-deployed engineers to deliver measurable brand results, develop repeatable vertical playbooks, design new customer use cases, and influence the product roadmap. This is a senior individual contributor role based in or requiring relocation to New York City.

Founding Head of Marketing will build a full-stack, data-driven growth engine: content/SEO, funnels & landing pages, lifecycle/email, product marketing, sales enablement, launches, pricing support, tracking/attribution, and direct paid/PR/creative partners. You will set GTM engineering roadmap and systematize founder amplification to drive qualified pipeline.

Lead product for a zero-to-one agentic marketing platform. Own roadmap, define how AI agents and the consumer graph drive measurable marketing outcomes, coordinate data, engineering, revenue teams, and drive activation and success metrics (ROAS, time-to-value, campaign performance).

Design and own a multi-tenant data transformation platform: tenant onboarding, schema/ontology evolution, correctness guarantees, RBAC/isolation, agentic and API access, real-time sync, orchestration migration, and governance to scale data products for AI-driven marketing.

Own the full inbound sales cycle for Minerva's AI marketing platform: run discovery, deliver demos, scope POCs with engineering/data, close deals, manage CRM pipeline and forecasting, and relay customer feedback to product and data teams.

Build and deploy production-scale feature engineering pipelines and predictive models over terabytes of consumer data. Own end-to-end path from raw data to reliable features/models consumable by autonomous agents, improve income/wealth and propensity models, and help architect the lakehouse and data infrastructure to support agentic systems.

Own end-to-end consumer data domains: ingest, clean, model, and productionize derived attributes and pipelines. Investigate new data sources, ensure quality and provenance, and partner with engineers, data scientists and product teams to deliver trustworthy data products that power applications, agents, APIs and ML models.