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Associate Director, Data Strategy & Analytics

Darkroom
CompanyDarkroom
CategoryData & Analytics
LocationNew York
RemoteHybrid
EmploymentNot stated
LevelDirector
SalaryNot stated by the employer
Posted17 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
ABOUT DARKROOM Darkroom is the leading next-generation growth marketing firm engineering the brands of tomorrow. Founded in 2017, we set out to redefine what a modern agency could be, by replacing the inertia of legacy advertising behemoths with a model built for speed, intelligence, and measurable impact. At our core, Darkroom is a human services company powered by Shadow, a universal AI commerce layer that integrates executive-level strategy with proprietary agentic technology. This fusion enables our teams to deliver outsized returns by enhancing creative output, operational efficiency, and revenue generation across every stage of the customer journey. Our track record speaks for itself: billions in attributable revenue driven across e-commerce marketplaces, media networks, DTC ecosystems, and social commerce platforms. Every engagement feeds into our proprietary data infrastructure, enabling a continuous feedback loop that accelerates growth, improves margins, and compounds results across our client portfolio. What began as a boutique design studio has evolved into one of the fastest-growing private companies in America and among the most effective performance media agencies of the 2020s. Our founders were recognized by Forbes 30 Under 30 for advancing the intersection of technology, marketing, and advertising, cementing Darkroom's role as a defining player in the future of media innovation. ABOUT 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. The majority of your time (roughly 75%) is spent on the product: designing the metric logic, data schemas, and analytical models Shadow's agents reason with, and working directly with marketing teams to translate what they actually do into structure the product can act on. The remaining time (roughly 25%) is spent on measurement of live media programs — guiding incrementality testing, power analysis, and MMM work, and partnering with Paid Media and Growth Strategy to turn test results into budget decisions. 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. The product side of this role is not client-facing; the measurement side is internal-facing too, working through Darkroom's own media teams rather than owning client relationships directly. 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. 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. WHAT YOU'LL OWN Product - 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 attribut
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