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Senior Data Scientist

About us:

RevenueCat makes building, analyzing, and growing mobile subscriptions easy. We launched as part of Y Combinator's summer 2018 batch and today are handling more than $4B of in-app purchases annually across thousands of apps.

We are a mission driven, remote-first company that is building the standard for mobile subscription infrastructure. Top apps like VSCO, Notion, and ClassDojo count on RevenueCat to power their subscriptions at scale.

Our 80 team members (and growing!) are located all over the world, from San Francisco to Madrid to Taipei. We're a close-knit, product-driven team, and we strive to live our core values: Customer Obsession, Always Be Shipping, Own It, and Balance.

We are looking for an experienced Senior Data Scientist to help us enable developers to make better decisions by using the unique data we have collected across the mobile subscription ecosystem. You will form part of our recently established Data team partnering closely with the product team to shape the future data features of our product. 

To achieve this, your work will involve creating data models, dashboards, and reports that power insights helping our customers make data-driven decisions to improve the overall user experience and maximise the product's value. We will do so by shipping data-enabled features, for example Lifetime Value (LTV) prediction, appraising the reliability of experiment results, or benchmarking. 

Our data tech stack includes a Python backend for development, a PostgreSQL production database for reliable data management, and a Snowflake data warehouse for scalable analytics. We leverage dbt for efficient data transformation, all on AWS for enhanced performance and scalability. We are in the process of enhancing our stack by integrating SageMaker and expanding our capabilities in the machine learning space.

About you:

  • You are proficient in SQL and are comfortable with data modeling
  • You have experience building predictive models
  • You have built production-ready data pipelines and Python models
  • You are driven by creating value for customers, not just scientific accuracy and you see perfect as the enemy of done
  • You are comfortable with ambiguity, lack of structure, and an environment where you can (and have to) build a lot from scratch
  • You have a proven ability to facilitate data-informed discussions between stakeholders across the organisation, through effective storytelling with meaningful insights
  • You are interested in the consumer mobile subscription ecosystem and are excited to explore the data we have

In the first month, you'll:

  • Understand our data models
  • Get to know the team
  • Ramp up on the ongoing data feature work

Within the first 3 months, you'll:

  • Work with our product, analytics and engineering teams to improve our data pipelines for data science features
  • Launch your own explorations into our data to fulfill your own curiosity

Within the first 6 months, you'll:

  • Meaningfully contribute to shipping a data feature to thousands of developers
  • Contribute to the roadmap of the data team
  • Ship, own, and continuously improve predictive models powering customer facing features
  • Contribute to architecting and further developing our data tech stack

Within the first 12 months, you'll:

  • Propose, design, and develop new data driven features from idea to shipping
  • Push the boundaries of how we are utilizing our data to help developers make more money

What we offer:

  • $185,000 USD salary regardless of your location
  • Competitive equity in a fast-growing, Series C startup backed by top tier investors including Y Combinator
  • 10 year window to exercise vested equity options
  • Fully remote work environment that promotes autonomy and flexibility
  • Suggested 4 to 5 weeks time off to recharge and focus on mental, physical, and emotional health
  • $2,000 USD to build your personal workspace
  • $1,000 USD annual stipend for your continuous learning and growth

 

Curious about the interview process? Discover more in our blog post about how we hire and learn tips to help you succeed.

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