Forward-Deployed Marketer
Mid-level Marketing (General) role at Darkroom. New York · full-time · $180,000 base.
Growth Roles summary, based on the employer's posting.
What you'll do
- Build the analytical models and metric logic that Shadow's agent reasons with, from raw platform data to decision-ready insight
- Cover contribution margin, acquisition truth, cohort LTV and payback, spend efficiency, and incrementality testing
- Define schemas that connect creative, channel, financial and customer data into a queryable view of a brand
- Decide what's load-bearing versus noise and compute metrics that hold up under operator scrutiny
- Spec the models, then work with data eng on pipelines and the AI team to wire them into agent skills
What you bring
- Ran growth at high-growth DTC or omni-channel brands, managing paid media hands-on rather than supervising others
- Fluency across the whole marketing mix, thinking in MER, CM and LTV rather than platform ROAS
- Genuine data science skills: SQL, Python notebooks, statistical reasoning, and validating models against messy data
- A knack for turning marketer intuition into rigorous structure, with clear opinions on which metrics matter
Who this fits
This suits a seasoned growth marketer who wants to build systems rather than manage accounts. It's not client-facing, and you report directly to Shadow's CEO. You'll thrive if you're entrepreneurial, ship production-grade work, and already embed AI into your workflows. The role is based in New York on a hybrid basis.
From the employer
What we're building
We're empowering small teams with technology that makes it easier to market and grow businesses. Our current focus is to help consumer brands shift from "workflow automation" to "agent management" within their marketing operations. Shadow is the AI coordination layer — providing shared AI memory, centralized agent control, and model orchestration for marketing teams.
Why join Shadow?
Product Ownership You'll ship production code daily and help steer key product and technical decisions.
Shape the Engineering Culture You'll influence how we work—tools, processes, standards, and hiring.
Work with Challenger Consumer Brands Talk directly to customers (CEOs, CMOs, VP's) of fast-growing consumer brands—some doing $80M–$500M in revenue.
The agency behind the product
Shadow is built alongside Darkroom — a performance marketing agency that's been operating for 10 years, employs 100+ people, runs 100+ clients at a time, and has worked with over 1,000 consumer brands. That's our edge: Shadow isn't a generic AI wrapper, it's a decade of real campaign tradecraft being codified into a system. Darkroom is both our proving ground and our first user. This role plugs directly into that knowledge and turns it into product.
The role
Part senior growth marketer, part data scientist, part applied-AI builder — you turn the way elite marketers think into the data models, metrics, and schemas that power Shadow's intelligence layer. You report directly to the CEO of Shadow.
This is for someone who's spent years in the work and now wants to lean into the technology — leveraging hard-won marketing experience to build, not to manage accounts. This is not a client-facing role.
What you'll own
Design the analytical models and metric logic the agent reasons with — contribution margin (CM3), acquisition truth (aMER, NCAC), cohort LTV/payback, ad spend efficiency and marginal-return analysis, incrementality testing (geo lifts, conversion-lift, MMM calibration) — from raw platform data to decision-ready insight.
Define the schemas that encode marketing tradecraft: how creative, channel, financial, and customer data connect into a queryable picture of a brand.
Own accuracy and judgment — what's load-bearing vs. noise, where attribution lies, how to compute metrics that survive operator scrutiny.
Spec the model; partner with data eng to build the pipeline and the AI team to wire it into agent skills.
Must have
Ran growth at one or more high-growth DTC / omni-channel consumer brands — you've managed paid media tactically, not just supervised people who did.
Fluency across the full marketing mix (Meta + Google, plus TikTok, email/SMS, marketplace, organic) — you think in MER/CM/LTV, not platform ROAS.
Real data science chops: SQL + Python/notebooks, statistical reasoning, building and validating metric models against messy real-world data.
Ability to translate between marketer intuition and rigorous structure — and a strong opinion about which metrics actually matter.
Nice to have
Familiarity with modern warehouse/analytics stacks (BigQuery, dbt) — enough to design schemas and collaborate with eng.
Agency or multi-brand background (pattern recognition across accounts).
Built attribution models, forecasting/MMM, or internal analytics dashboards.
Culture fit
You’re a power AI user. You've embedded AI into every workflow you touch and you think in systems — not one-off prompts, but repeatable structures that compound.
Entrepreneurial. You don't need much direction to move fast, you pivot when the situation demands it, and what you ship is production-grade, not a prototype you hand off for someone else to finish.
What we offer
Competitive salary (roles, responsibilities, and comp grow as we do)
Top-tier health, vision, dental insurance (US)
Regular team off-sites
Regular hack weeks
Compensation
Yearly compensation for this role is $180,000. Actual compensation will be determined based on experience, skills, and qualifications. This role is also eligible for performance-based compensation. A summary of benefits is listed above.
Equal Opportunity Statement
Darkroom is an equal opportunity workplace — we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national orientation, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.