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Marketing Science Analyst Jobs (NOW HIRING)

What You're Applying for As a Marketing Science Analyst on Triple Whale's Marketing Science team, you'll be a key operator within the Compass and Unified Measurement experience. This is a hands-on ...

The Senior Analyst, Marketing Science will use customer and marketing data to generate actionable insights and strategically drive Zoro's growth. This includes designing and running advanced ...

Marketing Science Lead

New York, NY · On-site

$180K - $275K/yr

About the Role Agentio is seeking a Marketing Science Lead to establish our measurement practice as ... You'll be the analytical architect who defines how clients measure success, influences what we ...

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Marketing Science Analyst information

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How much do marketing science analyst jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for marketing science analyst in the United States is $37.30, according to ZipRecruiter salary data. Most workers in this role earn between $27.88 and $43.99 per hour, depending on experience, location, and employer.

How does a Marketing Science Analyst typically collaborate with marketing and data teams?

Marketing Science Analysts work closely with both marketing strategists and data specialists to bridge the gap between raw data and actionable marketing insights. They often participate in cross-functional meetings, translating complex analytical findings into clear recommendations that marketers can use to optimize campaigns. Regular collaboration involves sharing reports, providing guidance on experiment design, and ensuring that data-driven decisions align with business goals. This teamwork fosters an environment where analytical perspectives enhance creative strategies, leading to more effective and measurable marketing outcomes.

What is a Marketing Science Analyst?

A Marketing Science Analyst is a professional who uses data analysis, statistics, and modeling techniques to help organizations understand their marketing performance and make data-driven decisions. They analyze customer behavior, campaign effectiveness, and market trends to provide actionable insights for optimizing marketing strategies. Their work often involves handling large datasets, using tools like SQL, Python, or R, and collaborating with marketing teams to improve ROI. By translating complex data into clear recommendations, they play a critical role in shaping successful marketing initiatives.

What are the key skills and qualifications needed to thrive as a Marketing Science Analyst, and why are they important?

To thrive as a Marketing Science Analyst, you need a solid background in statistics, data analysis, and marketing principles, often supported by a degree in a quantitative field like statistics, economics, or marketing analytics. Proficiency with analytical tools and programming languages such as SQL, Python, R, and data visualization platforms like Tableau is typically required. Strong problem-solving abilities, communication skills, and attention to detail help you translate complex data insights into actionable marketing strategies. These skills and qualities are crucial for driving data-informed decision-making and maximizing marketing effectiveness.
More about Marketing Science Analyst jobs
What cities are hiring for Marketing Science Analyst jobs? Cities with the most Marketing Science Analyst job openings:
Infographic showing various Marketing Science Analyst job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 5% Part Time, 1% Temporary, 5% Contract, and 1% Nights. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $77,589 per year, or $37.3 per hour.

Full-time

Posted 8 hours ago


Job description

What Do We Do?
Triple Whale is the complete intelligence platform that helps ecommerce brands confidently understand what's working in their business, what's not, and what they should do next.
We pull all your data into one place, give you the measurement tools to actually trust it, then use the smartest AI in the industry to translate it into insights and recommendations. From there, you get tools to put those insights to work - from AI agents that generate creative and take action on your behalf, to automations that make the rest of your tech stack smarter and more effective.
More than 60,000 brands like Pressed Juicery, Ouai and True Classic trust Triple Whale to grow faster with fewer resources - uncovering opportunities and acting on them at a scale that would be impossible manually.
What You're Applying for
As a Marketing Science Analyst on Triple Whale's Marketing Science team, you'll be a key operator within the Compass and Unified Measurement experience. This is a hands-on individual contributor role-you'll dive deep into the data, build and execute analyses, and help translate measurement outputs into decisions that brands can act on.
This role exists because brands at scale ($50M-$500M+ revenue, complex omnichannel operations) don't just need data-they need support turning measurement into decisions that hold up in the real world.
Reporting into our Marketing Science Lead, you'll partner closely with a Marketing Data Scientist, who owns model configuration and statistical rigor for MMM and incrementality testing. Your focus will be supporting operator translation, analysis execution, and helping shape the measurement roadmap for each customer.
You'll help deliver measurement strategy for a portfolio of Compass brands, from test design and MMM interpretation to attribution analysis and ongoing recommendations. You may also support select prospect conversations as a technical and analytical resource.
Sitting within Marketing Science, you'll work cross-functionally with Product, Data Science, and CSM-helping bridge the gap between customer complexity and Triple Whale's solutions.
What You'll Do
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?
What You'll Bring
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.
Strong differentiators
  • 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
Our Values
  • We Are Customer Obsessed: From our mission to every detailed project, everything we do is designed to create a positive impact for our customers.
  • We Move (Very!) Quickly: The speed at which we work, iterate, and deliver value is our most competitive advantage.
  • We Are Trustworthy: Candor, directness, and honest communication helps us learn, grow and improve so we can win together.
  • We Are Curious: We extend beyond our comfort zone and ask questions that guide us towards new, creative, and bold paths.
  • We Act Like A Mensch: We act with honor, integrity and empathy, and have deep respect for our customers and each other.

Triple Whale is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Join Us in Making Waves
If you're looking for more than just a job and want to be part of a movement reshaping the future of Ecommerce, Triple Whale is the place for you. We're on the lookout for driven, curious, and creative individuals ready to thrive in a fast-paced environment.
Referred? Got here thanks to a friend? Splash some gratitude their way! They'll need to submit your application through our referral system to make it official.
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