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Manager, Applied Science, Selling Partner Trust and Store Integrity Science

Amazon

Manager, Applied Science, Selling Partner Trust and Store Integrity Science

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

2w ago

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's customers and legitimate sellers while ensuring a fair and trusted shopping experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?

If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional Applied Science Manager who can revolutionize how we protect our marketplace through intelligent automation. You will lead a team of scientists and business analysts to develop and deploy state-of-the-art machine learning systems that analyze millions of seller interactions daily, ensuring the integrity and trustworthiness of Amazon's marketplace while scaling our operations to new heights. Your work will directly impact the safety and security of the shopping experience for hundreds of millions of customers worldwide, while supporting the growth of honest entrepreneurs and businesses.

  • Key job responsibilities
  • Set up the vision, mission and a 3-year science plan
  • Lead and manage a team of scientists, business analysts to build foundational and domain-specific solutions that prevent bad actors from operating in our store
  • Identify and prioritize high-impact opportunities for AI-driven transformation to make Amazon the most trusted store for our customers and selling partners
  • Mentor and guide team members to achieve their career goals and objectives

Basic Qualifications

  • 3+ years of scientists or machine learning engineers management experience
  • Knowledge of ML, NLP, Information Retrieval and Analytics

Preferred Qualifications

  • Experience building machine learning models or developing algorithms for business application
  • Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

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. 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, WA, Seattle - 183,800.00 - 248,700.00 USD annually

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About Amazon

Amazon

Amazon

Public

Amazon.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

M3

M4

M5

M6

Intern

L2 · Revenue Operations L2

0 reports

$163,421

total / year

Base

$65,368

Stock

$81,711

Bonus

$16,342

$114,395

$212,447

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