refresh

Trending Companies

Trending

Jobs

JobsAmazon

Applied Scientist, Seller Growth Science

Amazon

Applied Scientist, Seller Growth Science

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$142,800 - $193,200

Benefits & Perks

Competitive salary and bonus

Stock options

Remote options

Flexible PTO

Creative environment

Equity

Required Skills

Salesforce

Google Analytics

Hootsuite

Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources.
We are looking for an Applied Scientist II to work on our growth agent vision on seller recommendation to improve our SP growth strategy and drive new seller success. As a successful applied scientist on our talented team of applied scientists and economists, you will translate complex business problems into science solutions using a variety of machine learning techniques, and collaborate with engineering, research, and business teams to deliver impactful experiences on behalf of our sellers. You need to have deep understanding of the business domain and have the ability to bridge business needs with scientific approaches. You are also strong in machine learning methodology and scientific foundation with the ability to collaborate with engineering to put models in production to answer specific business questions. You excel at identifying the right ML techniques—whether supervised learning, causal inference, optimization, or other approaches—to solve diverse business challenges. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).
Key job responsibilities
As an Applied Scientist II in the team, you will:

  • Identify opportunities to improve SP growth and translate those opportunities into science problems.
  • Design and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.
  • Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
  • Be responsible for communicating our science innovations to the broader internal & external scientific community.

Basic Qualifications

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
  • Experience in solving business problems through machine learning, data mining and statistical algorithms

Preferred Qualifications

  • Experience using Unix/Linux
  • Experience in professional software development
  • Experience in designing experiments and statistical analysis of results
  • Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
  • Experience identifying opportunities to integrate AI solutions into products and services to drive business value.
    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 - 142,800.00 - 193,200.00 USD annually

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

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

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

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