Translate complex business problems into coherent, actionable quantitative solutions.
Implement, automate, and maintain reliable, performant, and end-to-end ML systems using software engineering and MLOps best practices.
Deliver clear, impactful insights to stakeholders through effective communication.
Collaborate with other data scientists / BI analysts on the team to operationalize quantitative solutions that inform strategy and optimize the user experience.
Promote best practices across the data science and product analytics team.
Build and maintain forecasting models that predict content performance ahead of release, helping guide content acquisition and programming decisions.
Build models to identify content traits and audience signals that predict what resonates most with each subscriber segment.
Build attribution models that quantify how specific titles drive P+ sign-ups and revenue to enable smarter content investment decisions.
Build models that predict user behavior throughout their subscription journey (e.g., sign-up, churn)
Build models to identify and measure high-value user actions and drivers of habit formation.
Create user segmentations that enable meaningful cohort-based targeting and support near-personalized experiences.

MS or Ph.D in Statistics/Data Science/Computer Science or related disciplines with specialization in machine learning techniques.
Experience with both supervised and unsupervised learning methodologies.
Experience in data collection, aggregation, analysis, visualization, productionalization, and monitoring of data science models.
Familiarity with well-known statistical and ML models and methods.
Ability to innovate without over-engineering.
Communicate concisely and persuasively with a variety of audiences.
Strong detail orientation with a penchant for data accuracy.
Experience with causal inference methodologies.
Experience applying forecasting models to media, content, or consumer behavior datasets.
Familiarity with holdout testing, uplift modeling, or other causal experimentation techniques.
Experience using Google Cloud Platform (BigQuery, VertexAI, and APIs).
Experience with integrating AI solutions into existing business processes.
Experience using project management tools like those from Atlassian (JIRA, Confluence)

Data Scientist

Key skills