Senior Data Science Manager, Duolingo

• We’re looking for an outstanding people leader in data science focusing on monetization and pricing
• Graduate degree in Data Science, Statistics, Economics, or a related field with 8+ years of relevant work experience; Or 10+ years of experience leading impactful teams and using analytics to solve product or business problems
• Experience coding (e.g., Python, R, SQL), querying databases, and statistical modeling
• Exceptional problem-solving abilities and the capacity to translate complex data into actionable insights
• Excellent verbal and written communication skills with the ability to collaborate effectively with both technical and non-technical partners
• Able to relocate to or work in our New York or Pittsburgh office

Desirable

• The ideal candidate will set strategic direction and lead a multi-disciplinary team of data scientists, own IC contributions of their own, and collaborate closely with company leadership to develop and deliver metrics, attribution models, and actionable business analyses
• They will evangelize scientific methods and influence strategic business decisions, with an appreciation for the behaviors of Duolingo users
• They will be a strong advocate and mentor for the Data Science & Analytics team and help advance their learning, creativity, and growth
• Lead a team of data scientists in monetization and pricing, and lead the cycle of translating ideas from concept to production-grade models and data science solutions, ensuring long-term viability and robustness
• Guide the team to apply advanced analytical methods, structural approaches, causal inference, and/or machine learning to model user behavior, and collaborate with product and engineering teams to develop scalable business frameworks and solutions
• Provide guidance and mentorship to junior staff and peers in the Data Science & Analytics function more broadly, fostering an environment of excellence, innovation, and collaboration
• Understand and lead the team in the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python)
• Build collaboration with data engineers and business intelligence to help the team turn insights into data products (e.g. data pipelines, algorithms, self-service dashboards)
• Effectively communicate findings and insights to executive partners and collaborate with product development teams to integrate them into decision-making
• Stay informed about advancements in data science and statistical methodologies to drive enhancements in internal tooling and methods at Duolingo