Machine Learning Scientist V, Ad Ranking

Netflix

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$466,000–$750,000 / yr
Posted
157 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $230k
This role $608k
$117k most similar roles pay here $818k

This role pays more than 99% of similar roles. Most pay $200,587–$260,150 — the shaded band above. At the midpoint, this role pays about $608k versus about $230k for comparable roles.

Based on 240 similar postings.

Employer

About Netflix

Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media

Netflix currently has 28 open roles on FindRole.

Listed pay typically runs $440,000–$750,000 across 27 roles with salary data.

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View all roles at Netflix

At a glance

TL;DR · Machine Learning Scientist V, Ad Ranking

Machine Learning Scientist 5 - Ad Ranking joins the Ad Ranking team within the Ads Data Science and Engineering organization to drive ad personalization through advanced machine learning and optimization algorithms. The role involves designing, building, training, and evaluating models on large-scale production data while developing online and offline evaluation frameworks to measure performance improvements. Key responsibilities include partnering with product teams to define optimization objectives and communicating technical decisions to various stakeholders. Candidates must possess an advanced degree in a quantitative field and demonstrate proficiency in Python, Scala, or Java. The role requires deep knowledge of machine learning, optimization, and data analysis techniques, specifically within the ad optimization stack including targeting, ranking, and bidding. This position focuses on solving problems related to identity science, user understanding, audience targeting, relevance, engagement prediction, and bidding pacing.

What you'll do

  • Design and implement machine learning and optimization algorithms to improve ad quality and performance.
  • Build, train, and evaluate models using large-scale production data.
  • Develop online and offline evaluation frameworks to measure the impact of model improvements.
  • Define optimization objectives, constraints, and trade-offs in collaboration with the product team.
  • Communicate technical decisions and experiment results to both technical and non-technical stakeholders.
  • Translate complex technical results into clear business impacts for various stakeholders.

What we're looking for

  • Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Proficiency in Python, Scala, or Java.
  • Deep knowledge of machine learning, optimization, and data analysis techniques.
  • Experience prototyping and deploying algorithms using large-scale production data.
  • Experience in an ad optimization stack, including targeting, ranking, and bidding.
  • Strong business acumen to translate technical results into business impact.
  • Excellent communication and collaboration skills.

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