Duolingo
Director of Data Science & Analytics, User Growth
Edtech.com's Summary
- Lead a team of 6-10 data scientists, manage performance, coach development, and hire talent.
- Set the analytical vision and roadmap aligned with company priorities for User Growth.
- Design, execute, and interpret experiments and causal analyses to inform user growth strategies.
- Develop and maintain forecasting systems in partnership with Finance and Product.
- Drive business intelligence strategy including metrics, dashboards, and analytical infrastructure.
- Translate complex analysis into clear narratives for senior leadership and influence strategic decisions.
- Collaborate with Product, Engineering, Design, Marketing, and Finance teams.
- Required skills: expertise in causal inference, statistical/ML modeling, experimentation, SQL, Python or R.
- Qualifications: 10+ years experience in data science/economics/analytics with 4+ years managing teams; graduate degree in relevant quantitative field.
- Compensation range: $244,000 to $366,000 USD annually.
Director of Data Science & Analytics, User Growth Full Description
Our mission at Duolingo is to develop the best education in the world and make it universally available. Itâs a big mission, and thatâs where you come in!
At Duolingo, youâll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. Youâll have limitless learning opportunities and daily collaborations with world-class minds â while doing work thatâs both meaningful and fun.
Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.
Read our blog to learn more.
About the role...
This person will own all aspects of product data science, forecasting, and business intelligence for User Growth. They will lead a team of 6 to 10 data scientists spanning staff to junior levels, with a mandate to coach, develop, and grow their careers while also expanding the team by hiring exceptional talent over time. The ideal candidate combines deep technical fluency in causal inference, statistical/ML modeling, and experimentation with genuine leadership ability: the kind of person who raises the bar for everyone around them.
This role reports to the Head of Data Science & Analytics and partners closely with executive leadership in Engineering, Product, Design, and Finance.
ð§ You will...
- 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.
- 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.
- 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.
- 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.
- 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.
- Translate complex analytical findings into clear narratives for senior leadership. Influence strategic decisions through a combination of technical depth and effective communication.
- Collaborate across organizational boundaries with Product Management, Engineering, Design, Marketing, and Finance to embed data science into every phase of product development.
- Stay current on advances in applied economics, statistical methodology, machine learning, and AI, and bring those advances into the team's practice where they create real value.
â You have...
- 10+ years of experience using data science, economics, or analytics to solve product or business problems, with at least 4 years managing and developing data science teams.
- A graduate degree in Economics, Statistics, Computer Science, Data Science, or a related quantitative field. A PhD is a strong signal but not a strict requirement; what matters is demonstrated depth and originality in analytical thinking.
- Deep expertise in causal inference, experimentation, and machine learning models. You are the person others come to when the measurement problem is hard.
- Proven ability to build, lead, and grow a high-performing data science team. You have a track record of hiring well, developing people across levels, and creating an environment where talented scientists do the best work of their careers.
- Strong command of SQL, Python or R, and the data engineering ecosystem. You do not need to write production pipelines, but you need to go deep when the work requires it.
- Exceptional communication skills, both written and verbal, with the ability to distill complex quantitative work into crisp, actionable insights for technical and non-technical audiences alike.
- Experience operating at a high-growth, data-intensive consumer technology company.
â Exceptional candidates will have...
- Experience developing and implementing a long-range analytical vision that shaped product strategy and business outcomes.
- Demonstrated success in building forecasting systems or attribution models at scale.
- A background in economics or a related field that brings structural thinking and causal reasoning to product problems, not just pattern recognition.
- Experience navigating the transition from growth-stage to scaled public company, including the analytical demands that come with investor-grade reporting and forecasting.
- Experience with AI and machine learning as applied to user behavior modeling, notification optimization, or personalization.
- An impressive Duolingo streak.
We post a multi-level salary range for all of our roles.
This is not inclusive of the rest of our awesome portfolio that includes equity compensation and world-class benefits. Our salary ranges are the same for all US locations. Your recruiter can share more details about the range for a specific level during the hiring process. The actual salary within the range is determined by many factors including but not limited to, skills, experience, education, and internal equity.
Take a peek at how we care for our employees' holistic well-being with our benefits here.
We will do everything we can within reason to make sure that your interview takes place in an environment that fairly and accurately assesses your skills. If you need assistance or accommodation, please contact accommodations@duolingo.com.
Duolingo is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
By applying for this position your data will be processed as per the Duolingo Applicant Privacy Notice.
Unfortunately, there is a rise in scammers pretending to be real Duolingo employees. Duolingo and our employees will never ask for your Social Security number, bank details, or passport info, and weâll never ask you to deposit a check, purchase equipment, or exchange money during the interview process. Real Duolingo employees always use an email that ends in @duolingo.com or @recruiting.duolingo.com. Stay alert and double-check these details before sharing any information.
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