TL;DR — You own the data behind how Lovable prices and packages. You turn usage, cost, and willingness-to-pay data into pricing and packaging bets, run the experiments to test them, and build the models that tell us what a change does to revenue and retention.

Why Lovable?

Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products, fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Lovable-built applications and websites are visited hundreds of millions of times a month, and our enterprise footprint is compounding fast. And we're just getting started.

We're a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.

What We're Looking For

Commercially-minded owner: A data scientist who owns pricing and packaging outcomes. You find the opportunity, model it, test it, and drive the change.
Economics fluency: Deep understanding of unit economics including LTV, margin, token and infrastructure cost, willingness to pay, discounting, and subscription or credit models.
Technical rigor: Strong SQL, Python, applied statistics, and experimentation skills. You are comfortable with causal questions where a clean A/B test is not always possible.
Systems builder: You build the systems that price and package, such as discounting or packaging models that run on user records, rather than just delivering one-off analyses.
Strategic judgment: An instinct for the tradeoff between growth and monetization, and the judgment to know when to prioritize each.
Entrepreneurial spirit: You thrive with autonomy and enjoy working closely with finance, product, and growth teams.

What You'll Do

Own the analytics behind pricing and packaging: what we charge, how we package it, and the impact of changes on revenue, conversion, and retention.
Build models for unit economics, willingness to pay, and price sensitivity, translating them into concrete pricing bets.
Design and execute pricing and packaging experiments, and act decisively on the results.
Build the systems that operationalize pricing decisions, such as personalized discounting based on user records.
Collaborate with finance, product, and growth to sequence and ship pricing changes effectively.

Our tech stack

We're building with tools that both humans and AI love: