Data Scientist, Pricing

About the role

Lovable is a Stockholm-based company that empowers individuals and organizations to build software using any programming language. Lovable-built applications and websites are visited hundreds of millions of times a month, and millions of people from solopreneurs to Fortune 100 teams use the platform to transform raw ideas into real products. The Data Scientist, Pricing role centers on owning the data infrastructure that drives how Lovable structures its pricing and product packages. This person will convert usage patterns, cost data, and customer willingness-to-pay signals into concrete pricing decisions, then validate those decisions through rigorous experimentation. The role requires close collaboration with finance, product, and growth teams to ensure pricing changes are sequenced and delivered effectively across all user segments. We are a small, talent-dense team building a generation-defining company from Stockholm, and we value extreme ownership, high velocity, and low-ego collaboration.

Key facts

What you'll do

• Own the analytics behind pricing and packaging decisions, including what Lovable charges and how it bundles features for users.
• Build models that estimate unit economics, willingness to pay, and price sensitivity for different customer segments and tiers.
• Translate model outputs into concrete pricing bets that balance revenue growth with customer retention goals over time.
• Design and execute pricing and packaging experiments, then act decisively on the results you observe from each test.
• Construct systems that operationalize pricing decisions, such as personalized discounting rules applied to individual user records in production.
• Collaborate with finance, product, and growth teams to plan and ship pricing changes in a coordinated and effective sequence.
• Analyze how pricing adjustments affect conversion rates, revenue, and long-term customer retention across all user tiers and segments.
• Develop frameworks for understanding token and infrastructure costs as they relate to overall unit economics and profit margins.
• Monitor and report on the impact of pricing experiments, providing clear recommendations to leadership and cross-functional stakeholders.
• Build and maintain dashboards that track pricing performance metrics and make insights accessible to partners across the organization.
• Evaluate subscription and credit-based pricing models to determine which structures best align with customer behavior and company objectives.
• Identify new packaging opportunities by analyzing usage data and willingness-to-pay signals from the existing customer base at scale.

Requirements

• Demonstrated experience as a data scientist with a focus on pricing, packaging, or monetization analytics in a product-driven company.
• Deep understanding of unit economics including LTV, margin, token costs, infrastructure cost, and willingness-to-pay estimation methods.
• Strong proficiency in SQL and Python for data analysis, statistical modeling, and building systems that operationalize decisions.
• Solid grounding in applied statistics and experimentation, including causal inference methods when clean A/B tests are not possible.
• Comfort working with pricing and packaging questions where clean randomized experiments are not always feasible or practical.
• Experience designing and building operational systems that embed pricing decisions into user-facing records or production configurations.
• Familiarity with subscription models, credit-based pricing, discounting strategies, and willingness-to-pay estimation techniques in real-world settings.
• A commercially minded mindset with the judgment to balance growth priorities against monetization objectives in dynamic environments.
• Ability to work autonomously while maintaining close and productive collaboration with finance, product, and growth stakeholders.
• Strong written and verbal communication skills, with the ability to present findings and recommendations to diverse audiences clearly.

Nice to have

• Experience working at a fast-growing startup or company undergoing rapid product and pricing evolution in a competitive market.
• Familiarity with GCP services such as BigQuery and PubSub for data warehousing and event streaming at scale.
• Background in building personalized or dynamic pricing models that operate at scale across large and diverse user populations.
• Prior experience with experimentation platforms and growth testing frameworks in a product-led or data-driven organization.
• Knowledge of Hex or similar analytics tools for building interactive data applications and shareable analytical dashboards.

Skills & tools

• SQL for querying large datasets and building analytical pipelines in a cloud warehouse environment with high reliability.
• Python for statistical modeling, data manipulation, and building systems that operationalize pricing decisions in production settings.
• BigQuery as a primary data warehouse for storing and analyzing pricing and usage data from millions of users.
• PubSub for event streaming and real-time data ingestion related to user interactions and pricing-related events.
• Hex for analytics and product data exploration, building interactive and shareable analytical workflows for the team.
• Lovable Apps as part of the product analytics and internal tooling ecosystem used by the data team.
• A/B and growth testing methodologies for designing and evaluating pricing experiments with statistical rigor.
• GCP cloud infrastructure for deploying and maintaining data systems that support pricing operations and decision-making.

Practical notes

• Applications must be submitted in English, as this is the company's working language for all daily communication and collaboration.
• The hiring process includes an intro call with recruiting, a conversation with the hiring manager, a take-home case study, and a Most Impressive Project session.
• Candidates should expect cross-functional interviews with the people they would work alongside, followed by a final conversation with company leadership.
• Lovable treats all candidates equally and welcomes applications from individuals of all backgrounds, experiences, and perspectives.
• The role is based in Stockholm, and the team values extreme ownership, high velocity, and low-ego collaboration as core cultural principles.