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# Principal Data Scientist

- **Company:** SKOOL INC.
- **Location:** Los Angeles, CA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Search Algorithms, Machine Learning, Scikit Learn, Real Time Data
- **Published:** September 23, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pm2yexvh63

## About the Role

* You have deep data science experience and a track record of using analysis, experiments, and models to grow a consumer product
 * You have hands-on experience building recommendation, matchmaking, ranking, or personalization systems
 * You have experience optimizing advertising campaigns, acquisition, or other performance marketing systems
 * You have a strong foundation in machine learning and statistical modeling using tools such as Python / scikit-learn
 * You favor quick action and experimentation over long analysis and can build enough conviction in your work to bet on it
 * You are comfortable managing real budget, being wrong, learning quickly, and making the next bet
 * You can own ambiguous problems, decide what matters, and move without waiting for permission
 * You are strong at data analysis and tool-agnostic. You care about accurate results and business impact more than a specific stack
 * You can write enough production-quality code to implement or partner closely on real-time solutions when offline analysis isn't enough

## Description

* Own data science work across growth, product, and user engagement, from analysis through measured results
 * Partner with Growth to optimize advertising daily, including adjusting spend, placing bets, and measuring lift
 * Build and improve recommendation, matchmaking, ranking, feed, and search algorithms that drive engagement and revenue
 * Design and run experiments, analyze results, and turn findings into clear product and business decisions
 * Develop predictive models for user intervention, activation, retention, and other key funnels
 * Use real-time data to find opportunities, test ideas quickly, and refine models based on outcomes


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