Data Scientist, Intern (PhD or Masters)

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 finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. 

Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.

  You will...

• Derive insights from data to influence product roadmaps and drive business results
• Apply advanced analytical methods, structural approaches, causal inference, and/or machine learning to model user behavior and estimate the impact of potential new feature implementations, and collaborate with product and engineering teams to develop solutions
• Evaluate product experiments to create and improve user experiences
• Communicate and present findings and recommendations to senior management 
• Help preserve our culture of fact-based decision making as we scale

  You have...

• Strong understanding of consumer digital products and an interest in applying advanced analytics and economics to business outcomes
• Pursuing a Masters or PhD degree (in at least the third year of PhD program) in a quantitative field (e.g. Economics, Finance, Statistics, Math, Linguistics, Computer Science, Computational Social Science), ideally planning to graduate in Spring/Summer 2026.  
• Previous experience analyzing large datasets and communicating results to technical and non-technical senior-level audiences
• Skilled in SQL, R or Python, and/or statistical methods to analyze behavioral data
• Enthusiasm for learning and sharing analytical methods to help grow a collaborative Data Science team and data-forward company culture
• Able to relocate to Pittsburgh or NYC for the internship

  Exceptional candidates will have...

• Experience with "big data" and cloud computing technologies like BigQuery, Snowflake, and/or dbt
• Experience articulating business questions and using available data to find answers that translate into product recommendations
• Self-starter, with a desire both to learn new techniques and guide others
• Previous experience/internships in applied business settings

  Why you'll love working here…

• Language learning opportunities
• Catered in-house lunches, and breakfast and dinner options
• Company-wide Hackathon
• Frequent company-wide dinners, monthly celebrations, social clubs, and so much more!

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 your recruiter.

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.

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.