Netflix is one of the world's leading entertainment services with over 247 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.
Everything that we build to delight our members, and all of the work we do to figure out how to do that better, relies on our extensive infrastructure, which spans what we rent from AWS to what we build ourselves (we operate our own custom-built content delivery network, Open Connect).
The Security, Platform and Open Connect Data Science and Engineering team partners with engineering teams across Netflix. Our goal is to use a data driven lens to enhance Netflix’s foundational technical infrastructure. We help design experiments, run analyses, productionize new data sources, and build analytic tooling that helps our partners innovate and build more performant, efficient and reliable systems.
We are seeking a Data Scientist who can help with foundational measurement problems in the infrastructure space. Our infrastructure is big and complex, and traditional approaches, such as member randomized A/B tests, are not always possible. This is an opportunity to partner with a cross-functional team to design, analyze, and build and enhance reusable tooling for our engineering partners. Experimentation techniques are critical to the long-term performance, cost management and reliability of our infrastructure, and you will be a key contributor in this area for Netflix.
In this role, you will:
- Build a rapport with engineering stakeholders by thoroughly understanding their domain and supporting them in designing, executing and analyzing experiments.
- Partner with other data scientists on the team, and with data scientists and engineers in the Experimentation Platform organization, to design and build scalable, self-serve experimentation tooling to meet infrastructure engineering needs.
- Design and rigorously validate new A/B testing methods and quasi-experiments.
- Be an advocate for the infrastructure experimentation space by thoroughly documenting your work, creating educational content, and exploring new ways to create more visibility for infrastructure experimentation across Netflix.
- Execute and present strong analysis and insights, share your work proactively and consistently seek feedback to refine your approach.
You Are
- Fascinated by understanding how complex systems work, but pragmatic in your solutions to experimentation problems on those systems.
- An impact-oriented, applied scientist. You know the theory behind experimentation but are motivated most by how the theory is used in practice.
- A great practitioner with a solid understanding of statistics.
- A good coder who likes to work with python, SQL (Trino, Spark SQL), and/or PySpark
- Comfortable with ambiguity and capable of navigating complex stakeholder relationships.
- Able to communicate your ideas clearly and succinctly with the right amount of detail to audiences with varying technical backgrounds.
Culture
Netflix'sculture is key to our success. We celebrate diversity, recognizing that diversity of thought and background builds stronger teams, and we approach inclusion equally seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
The overall market range for this role is typically $390,000 - $900,000.
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn morehere.