Data Science Leader – Video Delivery & Infrastructure 1225 views

How does Netflix provide a seamless viewing experience? Many complex, intricate engineering systems work together behind the scenes to deliver a high-quality experience. They encode studio content into files that are distributed to their content delivery network, then adaptively streamed by the many devices their members use to watch the content they love. Their data science and engineering team take a holistic approach to measure and improve these systems and how they directly impact the experience Netflix members have. Their goal is driving the quality of the viewing experience higher and higher across the variety of devices and networks their global members use.

What You’ll Do

They’re looking for accomplished data science and analytics leader for Netflix video delivery. Open Connect, its global content delivery network, serves 100% of Netflix content and makes up over 30% of downstream internet traffic at primetime in North America. This org operates like its own company within Netflix, and they need a leader to provide the vision for data science and analytics in this area.

You’ll lead a team of talented, senior individual contributors with a diverse set of skills across analytics, tooling, machine learning, and modeling and experimentation. You’ll partner with other data science teams and product engineering teams to optimize Netflix streaming with an eye toward scaling analytics and access to insights, innovating on methodologies, and finding new opportunities to apply high-impact science and analytics to Netflix challenges.

They’re looking for

• Experience hiring and leading high-caliber teams with diverse technical strengths
• Experience building and fostering an inclusive team culture
• Experience partnering with engineering or technical product teams to define and execute on strategic roadmaps
• Depth in at least one data science discipline (experimentation, modeling, analytics) and demonstrated strength applying that expertise to business areas
• Ability to autonomously find and execute on high-impact science and analytics opportunities