Marketing Experimentation & Optimization Lead

Hey there! We’re Fever , the world’s leading tech platform for culture and live entertainment. Our mission?

To democratize access to culture and entertainment. With our proprietary cutting-edge technology and data-driven approach, we’re revolutionizing the way people engage with live entertainment. Every month, our platform inspires over 300 million people in +55 countries (and counting) to discover unforgettable experiences while also empowering event creators with our data and technology, helping them scale, innovate, and enhance their events to reach new audiences.

Our results? C. Barcelona, and Primavera Sound, presented international award-winning experiences, and are backed by several leading global investors!

Impressive, right? To achieve our mission, we are looking for bar-raisers with a hands-on mindset who are eager to help shape the future of entertainment! Ready to be part of the experience?

What You Will Do

to help achieve Fever’s mission.

About The Role

Marketing is one of Fever's largest investments, and this role exists to answer the question the whole company relies on: does it actually work, and why? You'll follow efficiency across the full chain, from how much we spend and where, through the channel mix and platform setup, down to the creatives themselves. At our scale, a single structural improvement or one well-designed experiment can be worth millions.

The hard part is deciding under uncertainty. Ground truth is often unobservable, clean experiments are not always possible, and calls have to be made with imperfect data. Your value is bringing scientific method to exactly that: forming hypotheses, making your assumptions explicit, and designing the experiments that reveal what genuinely drives incremental results.

When a clean test is not feasible, you triangulate across methods instead. The domain is technical. You'll need to understand how Meta's and Google's delivery algorithms decide where budget flows, how pixels and conversion signals shape what they optimize toward, and how attribution windows distort what you see.

You don't need a marketing background. You need real curiosity about how these systems work and the analytical depth to connect them back to business outcomes. To be clear about what this is not : it is not a media-buying or campaign-management role, and it is not a model-building data-science role.

It's for a pragmatic problem-solver who wants to know the truth behind the numbers.

What You'Ll Do

Own the full efficiency chain, connecting spend levels, marketing mix, channel setup and creative performance into one coherent view, and pressure-test what our marketing-automation systems recommend. Turn open questions into clear test plans, decision frameworks and recommendations, with assumptions and trade-offs stated up front. Own the signal layer (pixels, events and custom conversions): how it's configured, what the algorithm optimizes toward, and how signal quality changes results.

Dig into the mechanics of paid platforms across Meta, Google and TikTok: campaign structure, bidding, budget optimization, audiences and catalogs. Design and run experiments that prove what works, from lift tests and geo-lifts to ablation tests and pre/post analyses, with clear metrics, statistical power and decision rules. Set the standards, playbooks and QA that make experiments rigorous and repeatable, and help raise the craft of the analysts you work with.

Must have A strong quantitative background: a degree in engineering, mathematics, physics, statistics, computer science or similar, or equivalent hands-on experience in analytical roles. 5+ years in analytics, experimentation, measurement or a comparable quantitative role. Solid experimentation foundations: A/B and geo experiments, lift and incrementality testing, statistical power and sample-size reasoning, control groups and baselines.