Senior Data Science Manager

Duolingo•Pittsburgh, PA

2d•$204,000 - $306,000

About The Position

Our mission at Duolingo is to develop the best education in the world and make it universally available. With over 500 million users and rapid expansion across new subjects and markets, Duolingo's growth trajectory demands world-class analytical leadership. We're hiring a Senior Data Science Manager to lead the data science function within our Growth pillar, one of the most consequential areas of the business. This person will own all aspects of product data science, forecasting, and business intelligence for User Growth. They will lead a team of 6 to 10 data scientists spanning staff to junior levels, with a mandate to coach, develop, and grow their careers while also expanding the team by hiring exceptional talent over time. The ideal candidate combines deep technical fluency in forecasting, statistical/ML modeling, and experimentation with genuine leadership ability: the kind of person who raises the bar for everyone around them. This role reports to the Head of Data Science & Analytics and partners closely with cross-functional leadership in Engineering, Product, Design, and Finance.

Requirements

Experience using data science and analytics to solve product and business problems.
Experience managing 5+ person data science teams.
A graduate degree in Data Science, Statistics, Economics, or a related quantitative field, or equivalent demonstrated expertise in formal analytical techniques.
Applied industry experience using causal inference, experimentation, and/or machine learning models. You routinely use analytical tools in messy real world settings where details, confounds, and the validity of assumptions matter.
Proven ability to build, lead, and grow a high-performing data science team. You have a track record of hiring well, developing people across levels, managing performance, and creating an environment where talented scientists do their best work.
Strong command of SQL, Python or R, and data/analytics engineering ecosystems. You do not need to write production pipelines, but you need to go deep when the work requires it.
Exceptional communication skills, both written and verbal, with the ability to distill complex quantitative work into crisp, actionable insights for diverse audiences.

Nice To Haves

Experience operating at a high-growth, data-intensive consumer technology company.
Experience developing and implementing a long-range analytical vision that shaped product strategy and business outcomes.
Demonstrated success in building forecasting systems or attribution models at scale.
Experience navigating the transition from growth-stage to scaled public company, including the analytical demands that come with investor-grade reporting and forecasting.
Experience with AI and machine learning as applied to user behavior modeling, notification optimization, or personalization.
An impressive Duolingo streak.

Responsibilities

Set the analytical vision and roadmap for User Growth data science, ensuring the team's work is tightly aligned with company-level priorities and pillar-level goals.
Lead a team of 6 to 10 data scientists. Build a culture of professional growth, intellectual rigor, creative problem-solving, and shipping impact. Grow the team over time by attracting and hiring outstanding talent.
Support and evolve the practice of embedding Data Scientists within product development teams, simultaneously maintaining strong stakeholder connection and function cohesion.
Own the design, execution, and interpretation of experiments and analyses that drive decisions on user acquisition, activation, retention, and reengagement. Improve and advocate for the methodological standards that ensure we learn reliably from every test.
Develop and maintain user growth forecasting systems. Partner with Finance and Product to deliver credible, timely forecasts of key growth metrics and ensure leadership has the quantitative foundation to set targets and allocate resources.
Drive business intelligence strategy within Growth, including the metrics layer, self-serve dashboards, and the analytical infrastructure that enables others to operate with data fluency.
Translate complex analytical findings into clear narratives for senior leadership and cross-functional partners. Influence strategic decisions through a combination of technical depth and effective communication.
Collaborate across organizational boundaries with Product Management, Engineering, Design, Marketing, and Finance to elevate every phase of product development.