Embedded Senior Data Scientist - Product & Growth

Duolingo is the world's most popular learning app, on a mission to develop the best education in the world and make it universally available. We rely on data-driven experimentation and Machine Learning to continuously improve learning efficacy and user engagement for over half a billion learners globally.

As a Staff Data Scientist on the Growth Data Science team, you will embed directly within one or more cross-functional product development teams. Combining deep technical fluency in data science, machine learning, and quantitative experimentation with acute product intuition, you will identify high-leverage growth opportunities, design robust A/B experiments, build predictive ML models, and translate complex data findings into actionable narratives that guide executive decision-making.

Key Responsibilities

• Embedded Product Analytics: Embed directly within product pods (working alongside Product Managers, Engineers, Designers, and Marketers) to formulate growth hypotheses, prioritize data science investments, and optimize user journeys.
• Predictive ML & Data Products: Build, validate, and deploy scalable machine learning models and predictive algorithms to personalize user experiences, predict retention, and improve user acquisition funnels.
• A/B Testing & Experimentation: Own end-to-end experimental design, power calculations, metric definition, and statistical evaluation for high-velocity A/B testing across core product surfaces.
• Analytical Infrastructure & Enablement: Develop standardized analytical definitions, methodological guidelines, self-service dashboards, and data pipelines that elevate data fluency across growth teams.
• Executive Communication: Distill complex quantitative models and statistical findings into crisp, actionable strategic narratives for executive leadership and cross-functional partners.
• Mentorship & Practice Leadership: Mentor junior data scientists and establish analytics best practices across the Growth Pillar and the broader Duolingo Data Science organization.

Requirements

Embedded Data Science & ML Depth

• Embedded Product Track Record: Demonstrated experience working as a Data Scientist embedded within software product development teams, using data to solve messy real-world user growth challenges.
• Advanced Quantitative Degree: Master’s degree or Ph.D. in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative field (or equivalent demonstrated expertise).
• Machine Learning Fluency: Practical fluency with standard machine learning algorithms, predictive modeling, regression analysis, classification, and statistical hypothesis testing.
• Modern Data Stack Mastery: Exceptional proficiency in SQL, Python or R, AI analysis tools, and modern data engineering ecosystems (Snowflake, dbt, Airflow).
• Executive Communication Skills: Outstanding written and verbal communication skills with a proven track record of translating complex analytical outputs into crisp business recommendations.

Work Logistics

• Passion for Duolingo's mission to democratize education worldwide.
• Ability to work from or relocate to Duolingo's product hubs in Pittsburgh, PA, New York City, NY, or work remotely within the United States.

Preferred Qualifications

• Experience operating within a high-growth consumer technology company, specifically supporting user acquisition, activation, or retention product pods.
• Hands-on experience building, maintaining, and deploying production ML models and real-time inference infrastructure.
• An impressive Duolingo streak!

Total Rewards & Benefits

• Compensation & Equity: Base salary of $182,800 – $247,300 USD supplemented by competitive equity grants.
• Holistic Well-Being: Choice of top-tier health plans with comprehensive medical, dental, and vision coverage for employees and eligible dependents.
• Culture & Perks: Catered in-house breakfast and lunch, language learning perks, bi-annual company hackathons, and active employee social clubs.
• Growth & Flexibility: Dedicated learning stipends, generous paid time off, and flexible remote work options.