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Senior Analytics Engineer (L5) - Ads

Netflix LogoNetflix
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At Netflix, we seek to entertain the world. We have more than 200 million members in 190 countries, reflecting that great stories can come from anywhere and be loved everywhere.  In April 2022, we announced that we are creating a new lower priced, ad-supported tier for our customers. We are now working toward our goal of providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers.

The Ads Data Science and Engineering team at Netflix’s mission is to help build the foundation of the ads business at Netflix. We conduct analyses and develop analytic tools, build predictive models and algorithms using machine learning, all with the goal of creating more choices and joy for our members.

As a Senior Analytics Engineer, you’ll design metrics, generate insights by scoping and executing deep dive analysis, and provide recommendations from a rigorous evaluation of product experiments. You’ll work closely with partner teams to build workflows, provide recommendations and drive success on end-to-end analytics initiatives in this 0 -1 space. This is an exciting opportunity to be a founding member of this new business area for Netflix!

In this role, you will:

  • Be a strategic partner for the business: Identify opportunities and create solutions to automate and scale ad hoc requests
  • Spearhead the creation of metrics that provide insight and help with decision-making
  • Develop high-impact dashboards and analyses to build visibility into the health of our ad platform, ad operations, and lead efforts to scale reporting through automation
  • Facilitate information self-service to business users through data pipelines and custom analytic tools

About you:

  • A senior analytics professional with a proven track record of data analysis, reporting and visualization (e.g. Tableau, D3)
  • A strong communicator with the ability to build meaningful stakeholder relationships
  • Enthusiastic about innovating in a fast-paced data and analytics space
  • Excited to learn about new fields, with the ability to be scrappy as needed
  • Comfortable with ambiguity; able to thrive with minimal oversight and process
  • Expertise in SQL, programming skills (e.g. Python, Scala), and some exposure to ETL and data warehousing concepts

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