> Markdown version of [/jobs/ext/1487348-machine-learning-python-scala-advertising-data-science](https://www.wearedevelopers.com/jobs/ext/1487348-machine-learning-python-scala-advertising-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # machine learning python scala advertising data science - **Company:** Netflix, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Data Analysis, Python (Programming Language), Machine Learning, Operational Databases, Yield Optimization, Information Technology, Optimization Algorithms, Machine Learning Operations - **Published:** July 29, 2026 - **Apply:** https://www.workingnomads.com/job/go/1758317/ ## About the Role * Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field. * 7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior staff-level scope and impact. * Deep knowledge of machine learning, optimization, and data analysis techniques. * Experience in ad optimization stack, e.g. targeting, ranking, bidding. Experience in Live ads is a huge plus. * Proven ability to set technical direction and influence roadmap across teams; experience serving as a vertical or staff-level technical lead is a strong plus. * Experience with prototyping and deploying algorithms using large-scale production data. * Proficiency in Python, Scala, or Java. * Strong business acumen and ability to translate technical results into business impact. * Excellent communication and collaboration skills. ## Description The Ad Supply & Decisioning team within the Ads Data Science and Engineering (DSE) organization drives ads growth by expanding ad inventory, optimizing member-ad matching, and maximizing long-term yield. The team spans three pillars, Ad Forecasting, Ad Ranking, and Ad Marketplace, and supports all ad surfaces, including live events such as sports, award shows, and cultural moments watched simultaneously by tens of millions of members around the world. Live advertising introduces a distinct class of problems: massive, unpredictable traffic spikes, global simultaneous delivery, hard real-time latency constraints, and the need to balance yield across direct and programmatic demand channels. We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our core Live Ads ML problem areas - forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization. In this role, you will partner directly with the Live Ads product team to define the ML technical roadmap and collaborate across horizontal pods within Ad Supply & Decisioning to drive solutions., * Define and drive the ML technical roadmap in close partnership with the Live Ads product team, aligning technical investments with business priorities and product direction. * Collaborate across horizontal pods to architect and deliver ML solutions spanning forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization. * 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, including senior leadership. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Quantum Tech: Preparing for the Next Leap](https://www.wearedevelopers.com/videos/1693-quantum-tech-preparing-for-the-next-leap) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [DevOps at Netflix](https://www.wearedevelopers.com/videos/270-devops-at-netflix) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [6 Reasons to Use Java For Your Next AI Project](https://www.wearedevelopers.com/magazine/111-6-reasons-to-use-java-for-your-next-ai-project) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)