Merciv
Product Marketing Manager
New York City
Sponsorship not specifiedDetected 4 days ago
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16Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- Our buyer is a VP of Consumer Insights (and their peers) at an enterprise consumer company.
- The sale is multi-stakeholder, long-cycle, and built on trust - we're asking teams to bring their proprietary data into our platform.
- Your job is to make our value legible to that buyer, in their language, and to arm the champion inside every account.
Responsibilities
- Own positioning and messaging: value maps that ladder every capability to a
- Build sales enablement: pitch narrative, decks, one-pagers, battlecards, objection
- Create mid-to-bottom-funnel content: solution and use-case pages, demo narratives,
- Partner directly with the product team as capabilities are developed, so what we build
Requirements
- 5+ years in product marketing at a high-growth tech startup, ideally B2B selling to
- Experience positioning for senior data, insights, or analytics audiences - rigorous
- Experience marketing trust: the messaging and proof (security, privacy, credibility)
- A track record with data-heavy B2B platforms - making complex products legible
- Shipped converting work you can tie to win-rate, conversion, or influenced pipeline -
Nice to have
- Long-cycle, referral-driven enterprise sales motions and multi-stakeholder deals.
- AI / data / research-tech category fluency.
- CPG / consumer-brand familiarity - it's where our buyers live.
- Experience standing up a PMM function from scratch, or operating as a team of one.
- Small team, high ownership, direct feedback.
- In-person in NYC.
- Evidence over opinion - message testing, win/loss, and conversion data settle
- This is a results-driven role: you'll be measured on influence - win rate, conversion,
Company info
- adoption, influenced pipeline - not raw lead volume.
This listing is sourced directly from Merciv's careers page and normalized into a canonical job model.