机器学习科学家 5 - 广告排名
Machine Learning Scientist 5 - Ad Ranking
在Netflix，我们的使命是娱乐全世界。我们正在书写下一章——突破叙事、全球粉丝和想象的边界，让不可能成为现实。我们是一支梦想团队，痴迷于探索创意、直觉和尖端技术融合时带来的不适感与兴奋感。加入我们，成为未来的一部分。
[我们在2022年11月推出了新的广告支持层级](https://deadline.com/2022/11/netflix-ads-launch-what-to-know-1235162223/)，并正在构建一个世界级的[广告技术生态系统](https://techcrunch.com/2024/05/15/netflix-in-house-advertising-technology-platform/)，为我们的会员提供更多内容消费选择。我们的新层级使我们能够在更低的价格点吸引新会员，同时为广告商提供一条有效触达深度参与用户群体的路径。
### 我们的团队：
广告排序团队隶属于广告数据科学与工程组织，是推动Netflix广告个性化的核心智能。该团队通过先进的机器学习和优化算法提升广告质量和性能，利用自有和外部数据信号。重点研究领域包括身份科学、用户理解、受众与定向、相关性与参与度预测，以及竞价与节奏控制。我们的目标是创造创新的数据驱动解决方案，为会员带来高度相关的广告体验，并为广告商实现显著的效果，同时保持Netflix体验所特有的高质量和个性化。
### 职责：
- 设计并实现机器学习和优化算法以提升广告质量和性能。
- 在大规模生产数据上构建、训练和评估模型。
- 开发在线和离线评估框架，严格衡量模型和算法改进的影响。
- 与产品团队紧密合作，定义符合产品和业务目标的优化目标、约束和权衡。
- 向技术和非技术利益相关者传达技术决策、权衡和实验结果，推动对机器学习驱动解决方案的理解和采用。
### 资格：
- 计算机科学、统计学、数学或相关定量领域的高级学位（博士或硕士）。
- 熟练掌握Python、Scala或Java。
- 深厚的机器学习知识，优化
查看英文原文
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
[We launched a new ad-supported tier](https://deadline.com/2022/11/netflix-ads-launch-what-to-know-1235162223/) in November 2022 and are building an in-house world-class [ad tech ecosystem](https://techcrunch.com/2024/05/15/netflix-in-house-advertising-technology-platform/) 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](https://jobs.netflix.com/work-life-philosophy).
Netflix is a unique culture and environment. Learn more [here](https://jobs.netflix.com/culture).
[Inclusion](https://about.netflix.com/en/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.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.