Data Scientist, Pricing
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 6, 2026. Lovable scores B on the Alion truth index.
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 is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started.
We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world.
Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software.
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:
Languages: SQL and Python
Warehouse & events: BigQuery, PubSub
Analytics & product: Hex, Lovable Apps
Experimentation: A/B and growth testing
Cloud: GCP
And we are always on the lookout for what's next.
How we hire
Fill in a short form and jump on an intro call with our recruiting team
A call with the hiring manager
A take-home case study
A Most Impressive Project session
Cross-functional interviews with the people you'd work with
A final conversation with leadership
About your application
Please submit your application in English. It's our company language, so you'll be speaking it daily if you join.
We treat all candidates equally. If you're interested, please apply through our careers portal.