Senior Manager, Ads Forecasting DSE

Netflix
USA - Remote$600k – $1050kPosted 7 April 2026

Job Description

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. Netflix is one of the world's leading entertainment services with over 260 million paid memberships in over 190 countries, enjoying TV series, films, and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time. In April 2022, we introduced a new, more affordable, ad-supported tier for our customers, marking a significant milestone for Netflix. Our focus is now on expanding choices for consumers and providing advertisers with a premium TV brand experience that surpasses traditional linear formats. The challenge ahead involves scaling our ad tech to maximize its impact on our business. The Ad Forecasting team in Ads Data Science and Engineering is responsible for building a scalable and extensible forecasting platform, and owning associated models for supply, demand, and revenue. These models generate crucial inputs for financial and strategy planning, ad marketplace operations, and ad delivery optimization. The team also drives the development of online and offline simulators to guide campaign setup and power scenario analysis and ad delivery policy improvements. We are looking for a visionary leader with strong domain expertise in forecasting to collaborate closely with partner teams and strategize on overarching business goals. Your team will be at the forefront of developing and implementing advanced forecasting algorithms, statistical models, and simulation tools, driving significant enhancements to our advertising systems. With a commitment to analytical rigor, your team will evaluate ideas, dissect problems, build workflows and tools, and lead end-to-end analytics initiatives in this transformative space. Responsibilities Hire, inspire, and grow high-performing data / ML / domain scientists, analysts, and managers. Lead strong partnerships with stakeholders from across the business - from product management, engineering, finance, consumer insights, content, and strategy. Instill an inclusive culture that is innovative and collaborative, both within your team and in the broader organization. Develop a team charter and roadmap that optimizes the impact of the team and reflects evolving business needs. Act as an ambassador between the Product, Engineering, Finance, Strategy, and Data & Insights teams by having a deep knowledge of how the Netflix Ads product works. Ensure that your team is producing consistently trustworthy and high-quality technical outputs that influence the business. The Ideal Candidate: Deep domain expert in ad forecasting and simulation. Demonstrated tenacity, resilience, and leadership experience that enables you to organize and drive cross-functional projects, overcome challenges, and propose solutions. Be both quantitative and qualitative. You should be able to quickly assess and understand complex systems, but also have high EQ, so that you can be a product ambassador to the rest of the organization, and our Hollywood and global partners. You are a player-coach. You can develop roadmaps and strategies, but also execute on technical work and ensure that your team produces consistent high-quality outputs. Superb communication skills - You must be able to cultivate strong working relationships, communicate effectively, write meticulously, and give outstanding presentations to both technical and creative audiences. Experience building and leading hybrid Science, ML and Algorithm teams in the ad space, with manager reports. Capacity and passion to translate business objectives into actionable analyse ... (truncated, view full listing at source)
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