Product Marketing Manager

Reposted 15 Days Ago
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New York, NY, USA
In-Office
140K-180K Annually
Mid level
Artificial Intelligence • Machine Learning • Software
Machine Learning for Data Fusion
The Role
The Product Marketing Manager will define Covariance's positioning, create sales enablement tools, drive GTM strategy, and provide market feedback.
Summary Generated by Built In
About Covariance

Covariance is the most advanced audience engine ever built. Our breakthrough AI customizes audiences for every brand and competitive set. Unlike traditional platforms that focus on existing customers, we give marketers a complete view of the entire market: competitors’ customers, your customers, and everyone else shopping in your space. Identify audiences you can win, activate them across channels, and measure lift – all powered by the Covariance Platform. Covariance turns population-scale data into real results.

+ We built the largest panel of anonymized, third-party consumer behavior data in the United States

+ We serve enterprise & mid-market retail, DTC, restaurants, transportation, subscription and more

+ Based on MIT research in specialized AI/ML for third-party data

+ Team of 30 headquartered in NYC

+ Winner of Harvard Business School Innovation Prize & named a Top 25 MIT startup to watch

The Opportunity

Covariance is hiring our first Product Marketing Manager to define how the world's largest brands understand (and buy) our AI-powered competitive & audience intelligence platform.

Built on MIT research in data-efficient machine learning, Covariance turns noisy, biased external data into the highest-fidelity audience signals in the market. This is a foundational role. You'll sit between Engineering, Product, and Sales to translate complex ML capabilities into buyer-ready positioning, sales-ready tools, and market-ready category leadership.

What You'll Own
  • Positioning & Messaging: define how Covariance shows up to enterprise buyers. Create the messaging architecture that underpins all GTM.
  • Sales Enablement: build the Covariance Playbook – decks, ROI calculators, competitive battlecards, demo scripts – that help sellers close against legacy solutions.
  • GTM Strategy by Vertical: develop segment-specific positioning and launch plans for core verticals. Partner with Sales to understand where we win and why.
  • Product-Market Feedback Loop: be the voice of the buyer internally. Translate customer objections, competitive gaps, and market signals into product roadmap input.
  • Category Creation: position Covariance as the leader in audience intelligence. Own thought leadership and competitive positioning.
What You Bring
  • 4-6 years in B2B product marketing, with at least 2 in adtech, martech, data platforms, or adjacent technical SaaS
  • Track record building sales enablement from scratch
  • Demonstrated ability to translate complex technical differentiation (ML, data infrastructure, identity resolution) into crisp buyer-facing narratives
  • Strong writing; you distill complexity into clarity
  • You use AI tools to move faster – this is part of your core workflow
  • Bonus: Experience selling to enterprise marketing, analytics, or data teams. Understanding of the identity/audience/measurement ecosystem.
Compensation & Benefits
  • Target annual cash compensation: $140,000 - $180,000 + competitive equity package
  • Free health, vision, dental insurance
  • 401k with match
  • Unlimited PTO + 13 company holidays 
  • Daily Grubhub lunch stipend
  • Pre-tax commuter benefits
Location

In-person at our NYC office strongly preferred.  Remote candidates who can spend some time in-office (e.g., monthly) will also be considered.

Top Skills

Adtech
AI
Data Platforms
Martech
Ml
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The Company
HQ: New York, New York
4 Employees

What We Do

Covariance delivers previously-impossible insights by combining our breakthroughs in machine learning with external data. We deliver a 360° view into any public or private company — as if you’re the CEO. Building on our MIT research, we are pioneers in data-efficient learning. Our patent-pending platform pushes the bounds of insights that machine learning can deliver when limited ground truth exists.

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