Director of Data Science & Analytics, User Growth

Duolingo Duolingo · Consumer · New York, NY +1 · Data Science + Analytics

Director of Data Science & Analytics, User Growth at Duolingo. This role involves leading a team of 6-10 data scientists, setting the analytical vision and roadmap for user growth, owning experiments and causal analyses, developing forecasting systems, driving business intelligence, and translating complex findings for senior leadership. The ideal candidate has deep technical fluency in causal inference, statistical/ML modeling, and experimentation, combined with strong leadership abilities. Experience with AI/ML applied to user behavior modeling, notification optimization, or personalization is a plus.

What you'd actually do

  1. Set the analytical vision and roadmap for User Growth data science, ensuring the team's work is tightly aligned with company-level priorities and pillar-level goals.
  2. Lead a team of 6 to 10 data scientists. Manage their performance, coach their development, and build a culture of intellectual rigor, creative problem-solving, and shipping impact. Grow the team over time by attracting and hiring outstanding talent.
  3. Own the design, execution, and interpretation of experiments and causal analyses that drive decisions on user acquisition, activation, retention, and reengagement. Establish and defend the methodological standards (A/B testing, guardrail metrics, measurement frameworks) that ensure we learn reliably from every test.
  4. Develop and maintain user growth forecasting systems. Partner with Finance and Product to deliver credible, timely forecasts of key growth metrics and ensure leadership has the quantitative foundation to set targets and allocate resources.
  5. Drive business intelligence strategy within Growth, including the metrics layer, self-serve dashboards, and the analytical infrastructure that enables the broader team to operate with data fluency.

Skills

Required

  • graduate degree in Economics, Statistics, Computer Science, Data Science, or a related quantitative field
  • deep expertise in causal inference, experimentation, and machine learning models
  • proven ability to build, lead, and grow a high-performing data science team
  • strong command of SQL, Python or R, and the data engineering ecosystem
  • exceptional communication skills, both written and verbal

Nice to have

  • PhD is a strong signal but not a strict requirement
  • developing and implementing a long-range analytical vision that shaped product strategy and business outcomes
  • building forecasting systems or attribution models at scale
  • background in economics or a related field that brings structural thinking and causal reasoning to product problems
  • navigating the transition from growth-stage to scaled public company
  • experience with AI and machine learning as applied to user behavior modeling, notification optimization, or personalization
  • An impressive Duolingo streak

What the JD emphasized

  • deep technical fluency in causal inference, statistical/ML modeling, and experimentation
  • proven ability to build, lead, and grow a high-performing data science team
  • strong command of SQL, Python or R, and the data engineering ecosystem
  • exceptional communication skills
  • experience operating at a high-growth, data-intensive consumer technology company
  • experience with AI and machine learning as applied to user behavior modeling, notification optimization, or personalization

Other signals

  • lead a team of 6 to 10 data scientists
  • own all aspects of product data science, forecasting, and business intelligence for User Growth
  • set the analytical vision and roadmap for User Growth data science
  • own the design, execution, and interpretation of experiments and causal analyses
  • develop and maintain user growth forecasting systems
  • drive business intelligence strategy within Growth
  • translate complex analytical findings into clear narratives for senior leadership
  • stay current on advances in applied economics, statistical methodology, machine learning, and AI