P

Posh

Ticketing and marketing platform for nightlife

Head of Data and ML

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Have 10+ years of experience in data, including 3+ years managing data science, machine learning, and/or data engineering teams at a high-growth consumer or marketplace company.
  • Be a former Staff-level individual contributor who can contribute technical judgment in model reviews, experiment readouts, and architecture discussions.
  • Have deep expertise in either causal inference or recommendation and ranking systems, and credibility in the other.
  • Have experience adopting AI-native data development practices and a clear view of the future of data roles, tooling, and team structure.
  • Have turned ambiguous product goals into technical roadmaps that shaped critical decisions.

Responsibilities

  • Own the entire data function, including the technical excellence and vision of the team responsible for event discovery, experimentation and measurement, and the company data platform.
  • Lead a multidisciplinary team of eight data scientists, machine learning engineers, and analytics/data engineers.
  • Balance team leadership with hands-on technical work as a player-coach.
  • Translate product vision into a technical roadmap the team supports.
  • Conduct analysis reviews, experiment critiques, and model evaluations, and build prototypes when useful.
  • Mentor senior individual contributors into leaders and help mid-level individual contributors advance.
  • Set a culture of rigor, urgency, and craft across the team’s disciplines.
  • Translate product vision into focused data and machine learning priorities, contextualize decisions for the team, assess product ideas for feasibility, cost, and learning value, and explain paths to enable currently infeasible ideas.
  • Own the data narrative in All Hands meetings, leadership reviews, and board updates.
  • Advise the team on ranking, recommendation, classification, and search algorithms, including problem framing, baselines, offline evaluation, and online testing.
  • Define metrics to evaluate improvements to event discovery.
  • Improve experiment design, metric selection, and analysis rigor.
  • Apply causal inference to questions that A/B tests cannot answer cleanly and improve understanding of ecosystem tradeoffs and marketplace dynamics.
  • Improve data infrastructure for AI and machine learning readiness, including the warehouse, feature pipelines, observability, and evaluation tooling.
  • Ensure models and AI features rely on trusted data and make build-versus-buy decisions.
  • Lead data and cross-functional partners in building the semantic layer and AI-native tools, including text-to-SQL, MCP, and agentic analytics.
  • Measure data adoption and address gaps.
  • Set expectations for quality across data science, machine learning, and data engineering; enable senior individual contributors to lead, support mid-level individual contributors’ development, and address difficult conversations promptly and carefully.

Desired Qualifications

  • Have built a semantic layer or AI evaluation frameworks in production.
  • Have entrepreneurial experience as part of a founding team or as a founder.
  • Have worked closely with a founder or CEO deeply involved in product, taste, and pace.

About the Company

Posh

Ticketing and marketing platform for nightlife

POSH.vip is a ticketing and marketing platform for nightlife and events. It helps event organizers manage ticket sales, guest lists, and promotions from one place. Features include a friendly guest list interface, SMS marketing, and social media integration (e.g., Instagram). The platform provides revenue analytics based on A/B testing and anonymous customer data, so organizers can make data-driven decisions. The business model combines subscription fees with a percentage of ticket sales, and it offers ticket tiers (GA and VIP) to segment buyers and optimize revenue. For example, GA and VIP tickets are priced at different levels, with potential revenue boosts cited for SMS tools (about 15% uplift) and guest lists (about 11% uplift). POSH’s goal is to help event curators around the world increase revenue and enhance the attendee experience by delivering practical tools that streamline marketing and ticketing in one platform.

Company size
201-500
Company stage
Series B
Total funding
$105M
Headquarters
New York City, New York
Founded
2019

Recently Posted Jobs

Explore more opportunities at Posh

See more jobs