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Netflix

Senior Manager, Ad Marketplace - Ads DSE

Reposted 11 Days Ago
Remote
Hiring Remotely in USA
360K-920K Annually
Senior level
Remote
Hiring Remotely in USA
360K-920K Annually
Senior level
Lead the Revenue Optimization team for Netflix's ad business, focusing on optimization algorithms and collaboration with various stakeholders to enhance advertising systems.
The summary above was generated by AI

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.

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 Marketplace team in Ads Data Science and Engineering plays a crucial role in Netflix's ad business growth. The mission for this team is to build a healthy, competitive, and innovative ad marketplace that balances long term Netflix revenue, member experience, and advertiser outcomes. The team will be responsible for ad auction design, dynamic pricing, and inventory / yield optimization. We are looking for a visionary leader with strong domain expertise in digital advertising marketplace optimization, to collaborate closely with partner teams and strategize on overarching business goals. Your team will be at the forefront of developing and implementing advanced optimization algorithms, statistical models and marketplace design, driving significant enhancements to our advertising systems. With a commitment to analytical rigor, your team will evaluate ideas, dissect problems, build workflows, provide recommendations, 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 DSE 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 marketplace design and optimization.

  • 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 analyses, and analytic results into business and product recommendations 

  • A passion for TV and movies and defining the future of entertainment

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 $600,000.00 - $1,050,000.00. 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.

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.

Top Skills

Analytical Models
Data Science
Machine Learning
Optimization Algorithms

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