The Data Scientist role at Netflix focuses on leading the partnership between the Messaging Data Science & Engineering team and the Consumer Messaging Program team. The main objective is to design and analyze experiments that enhance messaging strategies, ensuring that members receive relevant communications at the right time. This position requires collaboration with various teams to establish rigorous testing standards and measurement frameworks. The role also involves automating analysis processes and building scalable data solutions as the Messaging team expands.

• At least 5 years of relevant experience in experimentation and causal inference.
• Hands-on experience designing and analyzing experiments with causal inference techniques.
• Exceptional communication skills with both technical and non-technical audiences.
• Strong SQL and Python skills, including experience in building dashboards and automations.
• Ability to work independently and drive projects end-to-end.

• Design and run rigorous A/B tests evaluating Messaging strategies.
• Exercise causal inference techniques when clean tests are not feasible.
• Help define and evolve Messaging's experimentation standards and measurement framework.
• Own the code, data pipelines, and dataset enrichment for analyses.
• Automate recurring analysis work and create self-serve tools for the team.
• Translate open-ended business asks into well-scoped projects.
• Build data solutions that can scale as Messaging innovates.

• Employees at Netflix are often offered flexible, people-first benefits—unlimited time away, generous parental leave, global family-forming support, mental-health programs (mindfulness, free counseling/coaching), and health coverage tailored by country. Financially, Netflix pays at personal top-of-market and lets employees choose their mix of cash vs. fully-vested 10-year stock options, alongside donation and volunteer matching. Convenience perks can include trust-based travel/expense policies, relocation support, and “Work, Not Drive” rideshare flexibility.