Netflix is looking to solve the problem of enabling operational and creative excellence in the distribution and promotion of content on their service, and improving the discovery experience for their members.
Requirements
- Proven track record of researching and leading Experimentation and Causal Inference methods in ambiguous and complex business areas with a focus on technical rigor and robustness
- High proficiency in standard tech stack (e.g. Python, SQL), Experimentation (HTEs, multiple hypotheses correction), and common Causal Inference frameworks (e.g., propensity score matching, double machine learning)
- 4+ years of relevant experience with Experimentation and Causal Inference applications
Responsibilities
- Act as strategic partner for stakeholders and cross-functional collaborators to identify business opportunities and enhance business strategies with novel data science methods in the live event space
- Define and execute on roadmaps for measuring the impact of content merchandising and improving member experience with Causal Inference and Machine Learning
- Partner closely with other business leaders, product managers, and other data scientists to refine and scale Causal Inference model based systems
- Present your research and insights to all levels of the company
- Become a regional expert on Merchandising and Content Understanding Data Science and Engineering, helping educate and connect with regional offices
Other
- Exceptional communication and collaboration skills coupled with strong business acumen
- Comfortable with ambiguity; able to take ownership, and thrive with minimal oversight and process
- Netflix culture resonates with you
- 4+ years of relevant experience
