Marketing Scientist

Triple Whale

1d • Remote

About The Position

Triple Whale is a comprehensive intelligence platform designed to help e-commerce brands understand their business performance, identify areas for improvement, and make informed decisions. The platform integrates data, provides reliable measurement tools, and utilizes AI to deliver insights and recommendations. It also offers tools for AI-driven creative generation, automated actions, and enhancing the effectiveness of the tech stack. Over 60,000 brands trust Triple Whale to accelerate growth by uncovering and acting on opportunities at scale.

As a Marketing Science Analyst on the Marketing Science team, you will be a key operator within the Compass and Unified Measurement experience. This is a hands-on individual contributor role focused on diving deep into data, building and executing analyses, and translating measurement outputs into actionable decisions for brands. This role is crucial for brands with significant revenue ($50M–$500M+) and complex omnichannel operations that require support in turning measurement into real-world decisions. Reporting to the Marketing Science Lead, you will collaborate with a Marketing Data Scientist who handles model configuration and statistical rigor for MMM and incrementality testing. Your primary responsibilities will include supporting operator translation, executing analyses, and contributing to the measurement roadmap for each customer. You will deliver measurement strategies for a portfolio of Compass brands, encompassing test design, MMM interpretation, attribution analysis, and ongoing recommendations. Additionally, you may provide technical and analytical support for prospect conversations. Within the Marketing Science team, you will work cross-functionally with Product, Data Science, and Customer Success Management (CSM) to bridge the gap between customer complexity and Triple Whale's solutions.

Requirements

• Real operator experience at scale: You've been accountable for marketing performance, not as an agency buyer or advisor, but as someone with skin in the game at a brand doing meaningful revenue. You've made budget calls with imperfect data, defended channel spend to a CFO, and felt the organizational complexity that makes good measurement advice hard to act on.
• Measurement literacy: You understand the difference between last-click, MTA, MMM, and incrementality testing, and which one answers which question. You can explain test confidence, null results, and attribution gaps in plain language. You don't need to build the models; you need to make them mean something to an operator who has to act on them.
• Paid media and channel expertise: 5+ years running or closely overseeing paid media across Meta, Google, TikTok, or similar platforms at meaningful scale. You understand platform mechanics, attribution windows, and reporting gaps, and you have formed, articulable opinions about how each platform works and what it systematically gets wrong.
• Omnichannel fluency: You understand what it means to run marketing across DTC, Amazon, wholesale, and retail simultaneously, and why the attribution problems that creates are genuinely hard. You don't assume digital-only measurement frameworks apply cleanly to brands with offline complexity.
• Executive-level communication: You can run a high-stakes call with a CFO, CMO, and media buyer all in the room, adjusting depth and framing for each without losing any of them. You can deliver hard news (a null result, a recommendation that contradicts their instincts) without losing the relationship.

Nice To Haves

• Direct experience at or with a brand doing $50M–$500M+ in revenue, especially with retail, wholesale, or Amazon complexity on top of DTC
• Hands-on familiarity with Triple Whale, Northbeam, Rockerbox, or similar multi-platform attribution tools, with genuine opinions about their tradeoffs
• Experience evaluating or acting on incrementality test results (GeoLift, holdout, synthetic control) in a context where the findings informed a real budget decision
• Comfort operating where the playbook is being built alongside the delivery

Responsibilities

• Lead measurement strategy for Compass brands
• Own the full measurement conversation arc, from kickoff and test design through results interpretation and what-comes-next recommendations, for a portfolio of 8–9 figure brands
• Translate MMM, incrementality, and attribution model outputs into operator-native decisions: not "here's what the model says," but "here's what it means for your channel mix and your next budget call"
• Sequence tests intelligently across channels based on the brand's spend levels, organizational capacity, and the questions that actually matter to their business right now
• Interpret results for non-technical stakeholders: explain what a null result means, what 80% confidence does and doesn't authorize, and how an Amazon halo effect finding changes cross-channel thinking
• Help brands build a measurement roadmap over time, not just run one-off tests
• Be the channel expert in the room
• Bring working knowledge of the channels these brands actually run, including Meta, Google, TikTok, YouTube, retail media, and AppLovin, with a clear understanding of what each platform reports, what it doesn't, and where platform-reported performance diverges from business reality
• Help brands with offline complexity (wholesale, retail, Amazon) think through measurement in contexts where digital-only frameworks don't cleanly apply
• Reframe the questions brands bring: not "is my Meta ROAS good?" but "are these campaigns driving incremental new customers, or harvesting the brand awareness I've already built?"
• Apply cross-brand pattern intelligence, without violating confidentiality, to contextualize what individual brands are seeing in their data
• Support sales as a subject matter expert
• Join high-value prospect conversations as the operator credibility voice, not to pitch product, but to make a $200M omnichannel brand feel genuinely understood before a deal decision gets made
• Ask the questions that open the conversation: the ones that show you understand what it actually feels like to run marketing at their scale, even before Triple Whale is fully on the table
• Translate Triple Whale's capabilities into their operational reality, not into feature descriptions
• Feed the product from the outside in
• Distinguish between product gaps and operator context gaps: not everything that confuses a brand is a product problem, and knowing the difference is what makes your feedback actually useful
• Name patterns when multiple brands at similar scale hit the same friction point, and bring them to the product team with enough context to inform prioritization
• Bring the organizational reality that product can't get from the inside: what does it feel like to act on an MMM recommendation when there are 14 stakeholders with opinions on the campaign structure?

Benefits

• We celebrate diversity and are committed to creating an inclusive environment for all employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed