Remote opportunity at
RevenueCatSenior Data Scientist, Product
RevenueCat operates as a leading monetization platform that supplies infrastructure and tooling for mobile app businesses. The organization processes over sixteen billion dollars in annual purchase…
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About This Role
RevenueCat operates as a leading monetization platform that supplies infrastructure and tooling for mobile app businesses. The organization processes over sixteen billion dollars in annual purchase volume and serves a diverse clientele ranging from independent developers to the OpenAI mobile team. Operating as a remote-first enterprise with a team exceeding one hundred fifty individuals distributed across more than twenty-five countries, RevenueCat builds systems that handle substantial monetary value and impact…
Job Description
RevenueCat operates as a leading monetization platform that supplies infrastructure and tooling for mobile app businesses. The organization processes over sixteen billion dollars in annual purchase volume and serves a diverse clientele ranging from independent developers to the OpenAI mobile team. Operating as a remote-first enterprise with a team exceeding one hundred fifty individuals distributed across more than twenty-five countries, RevenueCat builds systems that handle substantial monetary value and impact massive end-user bases.
The company seeks a Senior Data Scientist specializing in Product to join its remote team on a full-time basis with a salary of USD 220,000 per year. This position suits an independent, highly proactive individual who enjoys tackling messy data, navigating ambiguity, and collaborating closely with engineering and product departments. In this role, the professional will shape customer-facing features like LTV predictions, benchmarking, and experimentation frameworks, utilizing a data stack that features Python, PostgreSQL, Snowflake, dbt, and AWS.
Responsibilities
- Explore company data independently to uncover product opportunities and customer pain points
- Convert ambiguous business challenges into structured analyses, models, and practical recommendations
- Collaborate directly with product managers to help shape product roadmaps
- Design and deploy production-ready predictive and descriptive models for customer-facing features
- Formulate and assess statistical methodologies utilized in benchmarking, forecasting, and experimentation
- Share insights effectively with both technical and non-technical stakeholders
- Refine deployed models and features continually based on user feedback and real-world performance
Requirements
- Possess at least five years of professional experience working as a data scientist
- Demonstrate strong proficiency in SQL and data modeling
- Bring practical background in building and deploying predictive and descriptive models into production environments
- Show experience writing or collaborating on production-ready Python code
- Maintain a solid grasp of statistics and experimentation concepts
Qualifications
- Familiarity with Bayesian statistical approaches
- Experience operating within the consumer subscription ecosystem
Core Skills
Benefits
- Competitive equity in a Series C startup
- Ten-year window to exercise vested equity options
- Fully remote work environment
- Four to five weeks of flexible time off each year
- Paid desk at a co-working space
- Workspace budget and continuous learning stipend
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, RevenueCat operates as a remote-first team.
What is the salary for the Senior Data Scientist, Product role?
The position offers a salary of USD 220,000 per year, along with competitive equity.
What technical background is required for applicants?
Applicants must have at least five years of data science experience, strong SQL skills, experience deploying production models, Python coding capability, and a solid understanding of statistics and experimentation.
What benefits are provided?
Benefits include competitive equity with a ten-year exercise window, flexible time off of four to five weeks annually, a co-working space desk, and budgets for workspace and continuous learning.
Sample Interview Questions
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