About Content Understanding
is the world’s leading streaming entertainment service with 270 million paid memberships in over 190 countries, enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
Content Understanding (CU) is a data science team that brings together many disciplines to empower product innovation with AI and data. We are looking for a Data Scientist to join us on this journey. In this role, you will be part of the Product organization, working to inform product strategy and develop novel approaches to content understanding.
What you will do:
- Lead sophisticated research projects that address challenging, ambiguous problems in the domain of content understanding.
- Develop, validate, and advocate for novel approaches to measure, understand, and predict content attributes and their impact on member experience and business goals.
- Collaborate closely with cross-functional partners (e.g., engineering, research, product, design, content) to define problem spaces, develop hypotheses, implement solutions, and drive impact.
- Leverage ’s wealth of data to drive insights and inform strategy.
- Present findings and recommendations to diverse audiences, including senior leadership.
- Mentor and guide junior data scientists and contribute to the growth of the team’s technical capabilities.
Who you are:
- 8+ years of experience in a data science, quantitative research, or analytics role, preferably in the tech industry.
- Ph.D. or Master’s degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research, etc.).
- Strong background in statistical modeling, causal inference, and experimental design.
- Demonstrated ability to translate complex data into actionable insights and communicate them effectively to technical and non-technical audiences.
- Expertise in SQL and Python (or R).
- Experience with distributed data processing (e.g., Spark).
- Excellent communication, collaboration, and presentation skills.
- Self-starter, curious, and proactive.
- Experience working with content-related data or recommender systems is a plus, but not required.
Our compensation structure consists solely of an annual salary, a variable bonus, and equity.
You can learn more about our compensation philosophy here.
