Data Scientist 5 - Product

Netflix•Sudbury, MA

1d•$372,000 - $600,000

About The Position

The Member Applied Research Data Science and Engineering team drives foundational research to advance the measurement and understanding of member value. We guide optimal product decision-making while balancing trade-offs, and connect on-the-ground needs from individual teams to holistic priorities and methods shared across the Netflix ecosystem. We are seeking a Senior Data Scientist with strong causal inference and experimentation experience to advance our understanding of member engagement with a growing variety of available content and new interaction types. In this role, you will drive foundational research, new metric development, and experimentation strategies that directly guide decision-making across the Netflix product. You’ll work in a highly collaborative and cross-domain environment with other data scientists, data and analytics engineers, and business teams to accelerate our measurement capabilities and influence our strategy.

Requirements

Advanced degree in Statistics, Mathematics, Computer Science, Economics or related quantitative field.
5+ years of relevant experience focused on building and delivering real-world machine learning models with demonstrated impact.
Strong statistical knowledge and intuition - ideally utilized in experimentation or other product analytics settings.
Strong Quantitative Programming skills in a language such as Python.
Exceptional oral and written communication skills.
Passion for driving product vision and innovation strategy by leveraging a broad set of techniques and building strong partnership with stakeholders.
Strong product sense to balance between addressing stakeholder or test-specific needs and investing in scalable solutions to serve general use cases.
Ability to work independently and drive your own projects.
Embody Netflix values while bringing a new perspective to continue to improve our culture.

Responsibilities

Drive product innovation through robust measurement strategies across experimentation, modeling, and analytics to shape how our members experience a variety of content types.
Establish strong partnerships with stakeholders to ladder local developments into a holistic measurement approach.
Contribute new methodologies to our causal inference tooling.
Develop experimentation and measurement frameworks to increase the velocity of investments and aid complex decision-making.