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Applied Scientist, Operations Research, Modeling and Optimization (MOP)

Amazon

Applied Scientist, Operations Research, Modeling and Optimization (MOP)

Amazon

Bellevue, WA, USA

·

On-site

·

Full-time

·

1w ago

Required Skills

Python

Java

Linux

Amazon's Modeling and Optimization (MOP) team seeks motivated individual with strong analytical and algorithmic skills to optimize the global logistics network and its operations.

  • Key job responsibilities

  • Enhance global logistics network efficiency through data-driven simulation and optimization

  • Reduce variable costs by improving network design, inventory placement, process and operational planning, and resource allocation

  • Optimize capital investment through strategic fixed asset deployment planning

  • Develop metrics to quantify business impact of implemented solutions

  • A day in the life

  • Lead development of production-ready algorithms and scientific tools for under-the-roof (UTR) and network process analysis and optimization

  • Drive planning and execution decisions on operation timing and resource allocation to improve capacity, cost, and speed.

  • Manage customer interactions, promote science-based processes, and incorporate customer needs into tool improvements.

  • Partner with team members and customers to exercise judgment on appropriate analysis methods for various business requests.

  • Interact with and influence adjacent systems and tools, including those for long-term operating policies and daily capacity planning.

  • Blend scientific expertise with business acumen to deliver impactful solutions across the organization.

Basic Qualifications

  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • 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

Preferred Qualifications

  • Experience using Unix/Linux
  • Experience in professional software development
  • Experience applying mathematical programming, process simulation, and reinforcement learning to operations research and optimization under uncertainty in real-world applications

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, Bellevue - 142,800.00 - 193,200.00 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

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