Netflix

Data Scientist, Content Understanding

Netflix

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Salary

💰 $150,000 - $750,000 per year

Job Level

Mid-LevelSenior

Tech Stack

PythonSQL

About the role

  • 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

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
  • Exceptional communication and collaboration skills coupled with strong business acumen
  • Comfortable with ambiguity; able to take ownership, and thrive with minimal oversight and process
Benefits
  • You choose each year how much of your compensation you want in salary versus stock options

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
Causal InferenceMachine LearningExperimentationPythonSQLpropensity score matchingdouble machine learningcontent merchandisingdata science methodsdata engineering
Soft skills
communicationcollaborationbusiness acumenownershipadaptabilitystrategic thinkingproblem-solvingeducational skillsinsight presentationcross-functional teamwork