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Amazon's shopping experience is designed for shoppers who exactly know what they want. However, not all shopping journeys fit that mold - people shop to explore, discover, refine their tastes or just have fun. Today, Amazon does little to service this type of shopping behavior. We want to address this gap by introducing a new way to shop on Amazon - one that services the less utilitarian aspects of shopping by encouraging shoppers to explore and discover new brands and products by browsing branded content, enabling brands to share their story and connect with shoppers, while also building brand loyalty. As we create new, complementary shopping experiences, shoppers will be able to choose between buying and exploratory shopping, and seamlessly transition between the two. Our experiences power billions of brand impressions.
This year, we're building capabilities that enable brands to personalize their shopping experiences for different customer segments and optimize those experiences using machine learning. We're launching a platform where brands can define their own shopper segments—based on how customers arrive, their relationship with the brand, or their shopping behavior—and tailor content for each segment using natural language configuration. We're also building intelligent optimization that automatically tests different content variations, learns what drives the best results for each segment, and continuously adapts as shopper behavior changes. Throughout both efforts, we'll deliver analytics that show brands how each segment performs, enabling data-driven decisions about their marketing strategies.
We are looking for a seasoned TPM to partner with product, design, science, operations, product marketing, third party integrators and sales teams in building these new personalization and optimization capabilities. Given the strategic importance of this program for Advertising and Amazon overall, this role will have high visibility at senior leadership level. Given the early stage of the product, this provides opportunities to think big, and requires a high bar on customer obsession, bias for action, dive deep, insisting on highest standards, and earning trust. Our products and initiatives are highly strategic, and visible across Amazon's senior leadership. The role requires someone with a strong understanding of, and desire to deeply learn customer needs, experience building consumer facing products from the ground up, excellent analytic skills, technical depth to navigate distributed systems and machine learning applications, and the ability to build trusted relationships with internal and external partners at senior (director and VP) levels. Our ideal candidate will be self-motivated, highly goal-oriented, comfortable with ambiguity, and with a track record of delivering solid results. They should be excited about the use of GenAI in helping deliver fast and use GenAI themselves in their day to day work. If the challenge of building personalized brand experiences that will fundamentally change the way brands connect with shoppers on Amazon excites you – please get in touch!
Basic Qualifications
- 5+ years of technical product or program management experience
- 3+ years of software development experience
- 5+ years of technical program management working directly with software engineering teams experience
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience building and evaluating system-level technical design
- Experience developing and executing/delivering product and technical roadmaps
Preferred Qualifications
- 5+ years of project management disciplines including scope, schedule, budget, quality, along with risk and critical path management experience
- Experience defining KPI's/SLA's used to drive multi-million dollar businesses and reporting to senior leadership
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, BC, Vancouver - 128,100.00 - 214,000.00 CAD annually
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About 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+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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