$ cat jobs/senior-data-scientist-growth-forecasting-duolingo-90a4e3f264b8.json
Senior Data Scientist, Growth Forecasting
Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in! At Duolingo, you’ll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. You’ll have limitless learning opportunities and daily collaborations with world-class minds — while doing work that’s 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 be part of our Growth Data Science team, collaborating with peers and cross-functional partners in Product, Finance, and Strategy to continuously improve our forecasting capabilities. They will drive methodological advances and deliver trustworthy business-critical quarterly forecasts, built on a deep understanding of the dynamics of user growth across Duolingo’s product portfolio. 🧠 You will... Join a small team of data scientists focused on User Growth forecasting. Collaborate with peers and mentor junior data scientists to ensure that our forecasts remain trustworthy and reliably delivered. Work with diverse stakeholders to develop forecasts that reflect a deep understanding of our product development, big bets, and evolving business strategy. Translate complex analytical findings into clear narratives for senior leadership and cross-functional partners. Influence strategic decisions through a combination of technical depth and effective communication. Develop and validate methodological advances to our forecasts, aligning methodological strengths with business priorities. Build systems and processes that ensure our forecasting process is robust and repeatable. ✅ You have... Applied industry experience building forecasts in messy real world settings where details, confounds, and the validity of assumptions matte
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