Forward Deployed Marketer
Minerva
Forward Deployed Marketer
Minerva
AI-driven customer behavior modeling platform
Minerva builds AI for marketing leaders. We work together with marketers to automate and accelerate their workflows with AI agents. Our agents augment the end-to-end workflow of the marketer by automating analysis, campaign planning, activation, measurement and reporting.
Customers like the NBA, Ramp, Wander, Hard Rock Stadium Group and Luxury Presence use Minerva to develop a better understanding of their customers and introduce AI specifically built to understand the customer into their commercial organizations. Our campaigns outperform other tools because we built the entire stack: from identity to enrichment to data integration as well as agents to action and report on the analysis.
We've raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital and many others. Our team brings together operators and investors from Citadel, Dentsu, Bridgewater, Meta Superintelligence, Growthloop, Amazon and Lazard, alongside engineers and researchers from Berkeley, MIT, Stanford and Cambridge.
An agent that can do almost anything has the same problem as a blank page. Someone has to decide what it does first, and then build it so a marketing team actually uses it.
That’s this seat. You bring a marketer’s judgment and an engineer’s build skills, and you do the work inside our customers’ marketing teams. You scope every pilot and pick the campaign that will move a real number. Then you turn it into a working system on Minerva (the agents, the data, the audience, the measurement), and you show the customer everything else Minerva can do, so the next request comes from them.
You decide which workflows are worth building and which aren’t. Nobody files a ticket for you.
This is a senior individual contributor seat with no direct reports. You’ll work directly with the founders, alongside our account executives, account managers, solutions engineers and forward deployed engineers.
Scope every pilot. Sit in pre-sale with the AE and pick the use case that will move a brand-side number inside the trial window.
Turn the use case into a system. Break the customer’s workflow down: what the agents do, which data they read, what they hand back, where someone on the customer’s team signs off, and how you’ll know when the output starts to drift.
Ship systems, not demos. A use case is done when their team runs it every week and it holds up on their messy data. You’re done when they run the second one without you.
Make the call when a number isn’t moving. Every brand’s first-party data is shaped by its own history. You tell a data problem from a definition problem, send the first to the account’s solutions engineer or forward deployed engineer and fix the second yourself.
Build what they didn’t know to ask for. A lapsed-buyer audience that rebuilds itself from the order table every week and reports lift against a holdout. A renewal-risk list a ticketing team works from every Monday. When we have no play for it yet, you design it and the account team sells it. The account manager owns the relationship and renewal.
Make yourself unnecessary. For each vertical, write down which use case goes first, which audience definitions survive a real campaign and what the VP needs to see in week two. Then record the Loom and run the session, so their team and our AEs can run it without you.
Go back when the tools get better. The models and our product improve every month. Revisit the accounts you’ve already deployed and rebuild what’s now possible.
Feed product the specific thing. What you reached for in the middle of real work shapes what we build next.
You’ve owned a brand’s marketing outcome. A campaign or a whole function, with the target and the result in your name. Agency-side counts if the client’s number was yours. Supporting the person who owned it doesn’t.
You’ve shipped something a marketing team adopted. An agent or an internal tool that got past the demo: people used it every week and you can tie it to a number they cared about.
You build with AI yourself. Hands-on with model APIs or agent tools: prompt design, structured outputs, evals that tell you when it’s wrong. You work in things like Claude Code, Cursor, n8n, Lovable or Vercel. We test this live in the loop.
You understand the full cycle, from strategy through audience, activation and measurement, and you can speak to every stage without handing off.
You know enough about data to diagnose. You don’t need to fix a broken pipeline, but you can tell when one is the problem.
Located in or willing to relocate to New York City.
A marketing engineer, growth engineer or GTM engineer who came up as a marketer and wants a customer’s number in their name.
A client lead at a performance or lifecycle agency who has owned outcomes across several brands and is tired of handing off the recommendation.
A growth or lifecycle lead at a consumer brand who has run the full cycle on one brand’s data and wants to do it across many.
A solutions lead at a marketing data platform who came up in marketing and wants to own the outcome, not the implementation.
Or you don’t fit any of these neatly, but you can name the number you moved for a brand and show us something you built. Apply.
SQL, even basic. This is the highest-slope accelerant for this seat.
Time at a CDP, identity or martech company, on either side of the table.
First 90 days: you’re on every pilot scoping call. At least one brand-side number has moved because of a system you designed and their team now runs, and one vertical has a written playbook.
First 6 months: you can name the number you moved on every account you deployed this quarter. At least one expansion exists because you built something new. The roadmap carries items that trace back to you.
The number you own: brand-side outcomes moved per deployed account, per quarter.
$200,000–$240,000 base salary, depending on experience. Early-stage equity. Medical, dental and vision.
Skip the cover letter. Send us one marketing outcome you owned, for a campaign or a whole function: the number, what you built and what happened. If you were agency-side, tell us the client’s number and which part of it was yours. Applications without a number won’t be reviewed. If you’ve built something, link it. A repo or a Loom is plenty. Later in the process you’ll get a Minerva login and design a use case for a real account, from the audience through to how you’d measure it.
We work in person from our office at 300 Kent Avenue in Williamsburg, Brooklyn.
Minerva uses AI to model consumer behavior and deliver predictive insights for go-to-market teams. It blends a company’s existing customer data with Minerva’s high-fidelity consumer data in a privacy-conscious way, and builds custom predictive models with clients for different personas and products that run in real time through APIs to CRMs, marketing tools, and data warehouses. The platform stands out by involving clients in model development, providing hyper-granular customer context, and offering seamless data integrations. Its goal is to make consumer behavior observable, predictable, and actionable to help organizations improve segmentation, targeting, and personalization.
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