Director of Engineering, Personalization & Recommendation

San Francisco, CA
Data Science, Analytics – Machine Learning /
Full-time /
On-site

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In-Office Policy

  • This position requires in-person attendance, reporting to our San Francisco office a minimum of three days per week (Monday, Wednesday, and Thursday), or as required by Quizlet. Do you currently reside within a commutable distance?

Additional Questions

  • How did you hear about us?
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  • What city & state do you currently reside in?

Additional Information - Director of Engineering, Personalization & Recommendation

  • Describe the most significant personalization or recommendation system you were responsible for building and deploying. What was your specific leadership role, what business metrics (e.g., user engagement, conversion, revenue) did it improve, and by how much?
  • How many years of experience do you have in a leadership role where you were directly managing and mentoring a team of machine learning engineers?
  • Which of the following core machine learning concepts have you had direct, hands-on experience implementing in a production environment? Please check all that apply.
  • Briefly describe a situation where you translated a high-level business need (e.g., 'increase user retention') into a technical roadmap for a personalization or recommendation feature.

U.S. Equal Employment Opportunity information   (Completion is voluntary and will not subject you to adverse treatment)

Our company values diversity. To ensure that we comply with reporting requirements and to learn more about how we can increase diversity in our candidate pool, we invite you to voluntarily provide demographic information in a confidential survey at the end of this application. Providing this information is optional. It will not be accessible or used in the hiring process, and has no effect on your opportunity for employment.