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Staff Growth Data Scientist, Monetization
What you will do
- Build pricing algorithms to manage fee configurations on marketplaces dynamically
- Develop monetization strategies that strike a balance between volume and margin, considering factors such as competitor prices, purchase order size, payment methods, currency pairs, user types, and geographies.
- Conduct market research and competitive analysis to identify trends, opportunities, and potential areas for growth
- Build crawlers and competitive intelligence tools to provide MoonPay with deep insights on competitor behavior across the Web3 ecosystem
- Utilize data-driven insights to forecast, experiment, and demonstrate the incrementality of monetization strategies, making data-informed recommendations on revenue optimization opportunities.
- Build data pipelines and dashboards to give leadership visibility on the performance of pricing experiments
- Architect incentive and reward mechanisms tailored to boost retention, while obsessing over the finer details that elevate the end-to-end product experience
- Create monetization strategies for new product lines, leveraging robust margin simulations and detailed financial modeling to inform decision-making
- Structure B2B and enterprise agreements with rigor around unit economics, balancing growth ambitions with margin integrity
- Collaborate with cross-functional teams, including Product, Engineering, FP&A, Data, and BD, to implement and execute monetization strategies effectively
- Proven experience in growth analytics and monetization (pricing, promotions, rewards, and loyalty programs) functions, with examples of implementing successful monetization strategies within a Consumer product
- Track record of designing and implementing high-impact incentive and reward systems that drive user engagement and retention
- Hands-on experience in building adaptive, data-driven pricing algorithms tailored to marketplaces and dynamic conditions.
- Strong analytical and quantitative skills, with proficiency in elasticity modeling and a good grasp of statistics, experimentation, and causal inference
- Understanding of pricing strategies and revenue optimization in B2C / B2B2C / B2B environments, with more emphasis on B2C and B2B2C
- Excellent communication and presentation skills to effectively communicate strategies and recommendations to stakeholders.
- Ability to work in extremely fast-paced environments, managing multiple priorities and meeting deadlines.
- Proficiency in SQL (BigQuery), Python, Git/GitHub, and preferably Looker (Tableau or PowerBI are acceptable as well)
- Above average knowledge of DBT, Docker, GCP, and Airflow
- Experience in the cryptocurrency industry, fintech sector, or platform-type businesses is preferred but not required.
- Analytical mindset with a passion for data-driven decision-making.
- Strong strategic thinking and problem-solving abilities.
- Self-motivated and proactive, with a strong sense of ownership and accountability.
- Problem solver, grounded in user problems, combined with strong first principles thinking to drive efficient solutions
- Highly ambitious with a results-oriented attitude and continuous improvement mindset
- Python
- SQL (BigQuery)
- GCP
- EPPO for experimentation
- DBT, Docker, Cloud Run/Kubernetes, and Airflow for data orchestration and data pipelines
- Looker data visualization
- Git and GitHub for code collaboration
- Ability to leverage AI tools such as Cursor and LLMs in the day-to-day work
- Nice to have, but can be learned on the job:
- Experience with web and/or app Scraping
- TypeScript (just the ability to understand the logic, not necessarily write code)
- DataDog (just the ability to write queries)
- LaunchDarkly (just the ability to change feature flag rules manually or programmatically)
- Postman for testing API calls
What does a data scientist in web3 do?
A data scientist in web3 is a type of data scientist who focuses on working with data related to the development of web-based technologies and applications that are part of the larger web3 ecosystem
This can include working with data from decentralized applications (DApps), blockchain networks, and other types of distributed and decentralized systems
In general, a data scientist in web3 is responsible for using data analysis and machine learning techniques to help organizations and individuals understand, interpret, and make decisions based on the data generated by these systems
Some specific tasks that a data scientist in web3 might be involved in include developing predictive models, conducting research, and creating data visualizations.