Advance data-centric decision-making at Duolingo by developing and delivering metrics, attribution models, and actionable business analyses.
Requirements
- 5+ years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, and statistical modeling.
- Experience with "big data" and cloud computing technologies like Redshift, Snowflake, BigQuery.
- Experience training machine learning models and deploying them in production.
- Familiarity with AI tools such as Cursor, a knack for prompt engineering, and a desire to continue to innovate and learn in AI.
Responsibilities
- Lead the cycle of turning ideas into production-grade data science solutions, ensuring long-term viability and robustness.
- Apply advanced analytical methods, causal inference, machine learning, and AI to model user behavior, and partner with product and engineering teams to build scalable business frameworks and solutions.
- Drive the data lifecycle: Understand, extract, transform, and validate data across multiple sources via relevant tools (e.g., SQL, R, Python).
- Partner with data engineers and business intelligence to turn insights into data products (e.g. data pipelines, algorithms, self-service dashboards).
- Communicate findings effectively to executive partners and collaborate with product teams to integrate insights into strategy and decision-making.
- Stay on top of developments in statistical methods and LLMs, and drive continuous improvement in internal tools and analytical practices at Duolingo.
- Provide guidance and mentorship to junior data scientists, encouraging an environment of excellence, innovation, and collaboration.
Other
- Outstanding 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 and work in our New York office.
- Strong experience in developing and implementing an analytic vision to solve business-relevant problems.
- Ability to lead multiple complex work streams and develop partnerships across organizational boundaries.
