Head of Data & ML at Posh · LumiJobs

Responsibilities

As our Head of Data and ML, you will own the entire data function. You’ll be accountable for the technical excellence and vision of the team that builds event discovery for 1M MAUs, the experimentation and measurement that guide product investment, and the data platform the whole company relies on to make decisions.
This is a rare opportunity to lead a unified data organization, providing clear direction and impact across the business. You’ll lead a talented multi-disciplinary team of 8 data scientists, machine learning engineers, and analytics/data engineers. Your job is to keep the team’s bar and vision sharp as Posh scales: choosing the right problems, making sound decisions, and shipping work that moves the product forward.
Balancing team leadership with hands-on technical work as a true player-coach
Translating a product-oriented vision into a technical roadmap the team believes in
Working hands-on in analysis reviews, experiment critiques, model evaluations, and building prototypes yourself when it moves things forward
Mentoring senior ICs into leaders and helping mid-level ICs level up
Setting a culture of rigor, urgency, and craft across every discipline on the team
This role is in-person 5 days a week at our SoHo, NYC headquarters. Relocation bonuses are available for out-of-state candidates.
Be the technical translation layer: Turn the product vision into focused data and ML bets, and give the team the context to make good calls on their own. When product brings you an idea, you sharpen or debate it, say what’s possible, what it will cost, and what we’ll learn. When something isn’t possible yet, you can explain why and lay out the path to get there. Own the data narrative at All Hands, leadership reviews, and board updates.
Build Posh’s discovery and search systems: Advise the team as they build our ranking, recommendation, classification, and search algorithms, from problem framing and baselines to offline evaluation and online testing. Define the metrics that prove discovery is getting better every quarter.
Make experimentation a source of truth: Raise the rigor of experiment design, metric selection, and analysis. Bring causal inference to the questions A/B tests can’t answer cleanly, so product and engineering investment follows real evidence. Improve our understanding of ecosystem tradeoffs and marketplace dynamics.
Scale the data and ML foundation: improve our data infrastructure, with a focus on AI/ML readiness - from our warehouse to feature pipelines, observability, and evaluation tooling. Make sure every model and AI feature we ship is built on data we trust. Make build-vs-buy calls along the way.

Head of Data & ML

Responsibilities

Qualification

Required

Benefits

Company

Posh

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