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Principal Product Manager Tech - Ad Server, Publisher Decision Engine
- We are seeking a Principal PMT for the Publisher Decision Engine
- Ad Server team to own and improve Programmatic Guaranteed deal delivery, which is a key offering from Amazon Ads that enables publishers to monetize their inventory.
Pub Tech (Publisher Technology) builds and operates extensible services that empower publishers (like Prime Video, Twitch, Tubi, and Paramount+) to improve the monetization of their customer experiences, along with the experiences themselves. Pub Tech offers various deal products that enable publishers to package inventory and sell it to advertisers. A key deal offering is the Programmatic Guaranteed (PG) deal, which allows publishers to sell an impression guarantee to advertisers for a given flight duration and price. PG deals are expected to deliver 100% of the impressions promised for all deals. Not meeting PG deal delivery targets could result in advertisers redistributing their budgets, which impacts revenue for both Amazon and the respective publishers.
Key job responsibilities
The Amazon Ads and Pub Tech Ad Server team owns and operates multiple algorithms that work together to optimize Programmatic Guaranteed (PG) deal delivery. These algorithms incorporate PG deal forecasts to determine how to pace deals toward their impression and spend targets, set appropriate impression goals, and select which PG deal(s) to serve for each incoming bid request.
As a PM of PG deal deliver in the Ad server team, your key responsibilities will include:
1. Creating a roadmap to improve current PG Deal Delivery Rates across our advertisers.
2. Design current algorithm inputs and outputs and leverage controller theory to improve PG deal delivery.
3. Define requirements for algorithms that account for seasonality, trends, advertiser delivery expectations (even, front loaded, etc), revenue implications and others .
4. Design experiments and iterate to improve on PG Deal Delivery.
A day in the life
Your morning will begin with analyzing Programmatic Guaranteed deal delivery metrics, identifying underperforming campaigns and diagnosing root causes across the pacing algorithms, delivery planner targets, and ad selection logic. As you identify root causes and systemic issues, you will collaborate with TPMs on the delivery program to align stakeholder expectations and troubleshoot critical delivery gaps. The afternoon involves cross-functional design reviews with engineering teams and applied science teams across delivery planner, pacing algorithms, deal selection, ad ranking, and bid request optimization systems. You will define requirements to iterate on the pacing algorithm implementation, ensuring it accounts for traffic seasonality and advertiser delivery preferences, while simultaneously working on new features like dynamic daily goal adjustments and improved PG deal prioritization logic. Your day closes with data deep-dives using analytics tools to measure the impact of recent algorithm changes on delivery rates and revenue, preparing recommendations for the next sprint's roadmap to drive the team closer to the delivery target for standard activation PG deals.
About the team
You'll join a group of product managers, applied scientists, and engineers Amazon's advertising ecosystem focused on improving PG deal delivery across. Our team owns the Publisher Ad server that owns forecasting total available impressions for a PG deal, Delivery planner that provides how many impressions a deal has to deliver to hit final impression target, deal selection and ad selection that selects the ad (that could be PG) for a given ad. These systems and algorithms enable Programmatic Guaranteed product delivery, helping advertisers secure inventory commitments with confidence while maximizing publisher yield. We work at the intersection of large-scale data engineering, statistical modeling, and product strategy. The team collaborates closely with yield optimization, sales, and publisher-facing teams to ensure our forecasts drive critical business decisions. We value technical depth, data-driven decision making, and the ability to translate complex analytical problems into practical product solutions.
Basic Qualifications
- Bachelor's degree
- Experience owning/driving roadmap strategy and definition
- Experience as a strong leader who can prioritize well, communicate clearly and effectively influence across cross-functional teams
- Experience directly working with engineering teams
- Experience in data analysis and leveraging analytics to make decisions
- Experience in working with science teams influencing the algorithm inputs and outputs
Preferred Qualifications
- Knowledge of data structures, algorithm design, statistics, and system design
- Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems
- Experience in programmatic advertising
- Experience in improving Pacing algorithms leveraging Controller Theory
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Sunnyvale - 206,900.00 - 279,900.00 USD annually
USA, NY, New York - 197,900.00 - 267,800.00 USD annually
USA, WA, SEATTLE - 179,900.00 - 243,400.00 USD annually
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企 业估值
评价
10条评价
3.4
10条评价
工作生活平衡
2.5
薪酬
4.2
企业文化
3.0
职业发展
3.8
管理层
2.7
65%
推荐率
优点
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
缺点
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
薪资范围
4个数据点
Junior/L3
M3
M4
M5
M6
Mid/L4
Senior/L5
Staff/L6
VP
Director
Junior/L3 · Product Manager L5
0份报告
$187,921
年薪总额
基本工资
-
股票
-
奖金
-
$159,732
$216,110
面试评价
6条评价
难度
4.0
/ 5
时长
21-35周
体验
正面 0%
中性 17%
负面 83%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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