Senior Data Scientist, Economics

Our mission at Duolingo is to develop the best education in the world and make it universally available. But we’ve got more left to do and that’s where you come in!

Duolingo is the world's most popular learning app. Beyond our core learning product, we also offer English proficiency testing with the Duolingo English Test, and are bringing new subjects into the Duolingo app, where people can develop their Math and Music skills.

We’re looking for an outstanding technical candidate in economics and data science who specializes in statistical modeling, causal inference, and / or structural analysis to advance data-centric decision-making at Duolingo.

The ideal candidate will have a background in the education field and / or in measuring learning gains. They will collaborate closely with executive leadership in Engineering and Product Management 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 and learning patterns 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.

We are passionate about educating our users, making fact-based decisions, and finding innovative solutions to complex problems.

We offer meaningful work, limitless learning opportunities, and collaboration with thoughtful peers. Come brighten your life and over half a billion more!

Read about our Data Scientist work on

What You’ll Do...

• Partner in leading the cycle of translating ideas from concept to production-grade economic models and data science solutions, ensuring long-term viability and robustness.
• Apply advanced analytical methods, structural approaches, causal inference, and / or machine learning to model user behavior, develop learning metrics, and identify learning improvements.
• Understand and lead the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python).

Independently format, re-structure, and / or validate data to ensure quality.

• Collaborate with data engineers and business intelligence to 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 applied economics and statistical methodologies to drive enhancements in internal tooling and methods at Duolingo.
• Provide guidance and mentorship to the Data Science & Analytics team, fostering an environment of excellence, innovation, and collaboration.

What We’re Looking For

• PhD in Economics, Statistics, Data Science, or a related quantitative field.
• 4 + years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, and economics / 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.

Why you’ll love working here

• Generous PTO and company holidays
• High quality medical, dental, and vision care
• Comprehensive mental health, backup care, and family forming support
• Paid parental leave for birthing and non-birthing parents
• Language learning opportunities
• Catered in-house lunches and breakfast
• Frequent company-wide dinners, monthly celebrations, social clubs, and so much more!

We invest in and support our Duos! This role is eligible for a robust compensation package of base salary, equity, and Duolingo’s world-class benefits.

The starting base salary range for this role is, $144,500 - $294,000. Actual salary may vary based on level, work experience, performance, and other factors evaluated during the hiring process.