Data Scientist, Pricing
Owns pricing and packaging analytics, models unit economics and willingness to pay, and runs experiments that guide revenue and retention decisions. The role requires strong SQL, Python, applied statistics, experimentation, and cross-functional commercial judgment.
About the job
Responsibilities
- Own the analytics behind pricing and packaging, including pricing, packaging, revenue, conversion, and retention impacts.
- Build models for unit economics, willingness to pay, and price sensitivity, translating findings into pricing decisions.
- Design and execute pricing and packaging experiments, then act on the results.
- Build systems that operationalize pricing decisions, including personalized discounting based on user records.
- Collaborate with finance, product, and growth teams to sequence and ship pricing changes.
Requirements
- Commercial ownership of pricing and packaging outcomes.
- Deep understanding of unit economics, including LTV, margin, token and infrastructure costs, willingness to pay, discounting, and subscription or credit models.
- Strong SQL, Python, applied statistics, and experimentation skills.
- Ability to address causal questions when a clean A/B test is not possible.
- Experience building production systems for pricing and packaging rather than only delivering one-off analyses.
- Strategic judgment regarding growth and monetization tradeoffs.
- Autonomy and effective collaboration with finance, product, and growth teams.
Technical Stack
- SQL
- Python
- BigQuery
- PubSub
- Hex
- Lovable Apps
- A/B testing
- Growth testing
- Google Cloud Platform (GCP)
Hiring Process
- Intro call with recruiting
- Hiring manager interview
- Take-home case study
- Most Impressive Project session
- Cross-functional interviews
- Final leadership conversation
Skills
SQL, Python, Applied Statistics, A/B Testing, BigQuery, Pub/Sub, Hex, Lovable Apps, GCP, Unit Economics, Pricing Models, Willingness To Pay, Price Sensitivity, Causal Inference, Personalized Discounting
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