Netflix

Machine Learning Scientist 5 - Ad Ranking

Netflix$466K — $500K+*
Media
Less than 5 years of experience
Job Overview by Ladders

Qualifications

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

Responsibilities

  • Design and implement machine learning and optimization algorithms to improve ad quality and performance.
  • Build, train, and evaluate models on large-scale production data.
  • Develop online and offline evaluation frameworks to measure impact of model improvements.
  • Partner closely with product team to define optimization objectives and trade-offs.
  • Communicate technical decisions to both technical and non-technical stakeholders.

Benefits

  • Comprehensive Health Plans and Mental Health support.
  • 401(k) Retirement Plan with employer match.
  • Stock Option Program.
  • Disability Programs and Family-forming benefits.
  • Paid leave of absence programs with 35 days PTO for hourly employees and flexible time off for salaried employees.
Full Job Description
We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.

Our Team:

The Ad Ranking team within the Ads Data Science and Engineering organization is the central intelligence driving ad personalization at Netflix. The team is responsible for enhancing ad quality and performance through advanced machine learning and optimization algorithms, utilizing both proprietary and external data signals. Key areas of focus include Identity Science, User Understanding, Audience & Targeting, Relevance & Engagement Prediction, and Bidding & Pacing. Our goal is to create innovative, data-driven solutions that deliver highly relevant ad experiences for our members and achieve impactful results for advertisers, all while upholding the exceptional quality and personalization characteristic of the Netflix experience.

Responsibilities:
  • Design and implement machine learning and optimization algorithms to improve ad quality and performance.
  • Build, train, and evaluate models on large-scale production data.
  • Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements.
  • Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals.
  • Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, driving understanding and adoption of ML-driven solutions.


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


Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

Job is open for no less than 7 days and will be removed when the position is filled.

About Netflix

Netflix, Inc. is an American media company founded on August 29, 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California, and currently based in Los Gatos, California, with production offices and stages at the Los Angeles-based Hollywood studios (formerly old Warner Brothers studios) and the Albuquerque Studios (formerly ABQ studios). It operates an eponymous over-the-top subscription video on-demand service, which showcases acquired and original programming as well as third-party content licensed from other production companies and distributors. Netflix is also the first streaming media company to be a member of the Motion Picture Association.
Learn more about Netflix
Size
11,300 employees
Market Cap
$127.6 billion
Industry
Net Income
$2.7 billion
Founded
1997
5 Year Trend
+27.5%
Revenue
$24.9 billion
NASDAQ

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