The New York Times

Programmatic Analyst

New York, NY

Sponsorship not specified$75k-$88kDetected 22 hours ago

Data VisualizationSales

About the role

This is a hybrid role based in our New York headquarters, VP of Revenue Operations.
You can typically expect to be in the office 3 days per week.

You will manage the daily programmatic platform management and operations, which include rule and deal optimizations, ad quality enforcement, and troubleshooting.
Partner with the Sales team to help assist and recommend programmatic inventory and targeting solutions.
Maintain our relationships with ad exchanges and supply side platforms (SSPs).
Special focus on deploying and maintaining programmatic technology solutions by testing partner's header bidding, price rules, and deal capabilities.
You will be the daily contact with supply side partners and support the sales team in programmatic conversations.
You will be a subject matter expert and programmatic sales specialist for the NYT data ad products, and be able to partner with Business Analytics to provide accurate and frequent analysis of programmatic optimizations and opportunities.
To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.

2+ years of experience in digital advertising or media
1+ years working with DMPs, ad exchanges, agency trading desks, DSPs and supply-side platforms (SSPs)
Experience with reporting and data visualization tools such as

Experience working in a high functioning team environment
We're excited to learn more about you and your experience.
If you're an Engineering candidate, we'll let you know what specific GenAI tools you are permitted to use for your technical assessment.
The New York Times Company is committed to being the world's best source of independent, reliable and quality journalism.
To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization.
We encourage people from all backgrounds to apply.
All applications will receive consideration for employment without regard to legally protected characteristics.
The U.S. Equal Employment Opportunity Commission (EEOC)'s Know Your Rights Poster is available here.

For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock.
$75,000 - $88,000 USD

For roles outside of the U.S., information on benefits will be provided during the interview process.

The mission of The New York Times is to seek the truth and help people understand the world.
That means independent journalism is at the heart of all we do as a company.
It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries.
It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination.
And it's why our business strategy centers on making journalism so good that it's worth paying for.
Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Commission (EEOC)'s Know Your Rights Poster is available here.
Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com.
The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
For information about The New York Times' privacy practices for job applicants click here.

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This listing is sourced directly from The New York Times's careers page and normalized into a canonical job model.