Jobs
Join Amazon's Rest of World Supply Chain Research team to revolutionize supply chain planning across multiple geographies including India, Japan, Mexico, Brazil, MENA, Australia, and Singapore. As an Operations Research Scientist, you'll develop optimization solutions using simulations, integer programming, and heuristic search to solve complex short-term capacity planning challenges that directly impact millions of customers worldwide.
Key job responsibilities
We are looking for an Operations Research Scientist to develop & support our Short term capacity planning initiatives using Simulations, Integer Programming, Linear Programming or Heuristic search. This Scientist, will work closely with our program partners to define business requirements, build data pipeline, write optimization code, deep dive on solution quality and drive adoption with operations.
The employee will also be responsible for interfacing with global science teams to help launch their tools to new geographies.
A day in the life
The employee will work with our program partners to find new opportunities for building/launching decision support tools for our Supply Chain planning teams. This will include
- Understanding the current planning process for program teams and tools available to them.
- Determining the gaps in the tools/decision making through data analysis or simulation systems.
- Determining the best possible tool to solve for the current gaps.
- Launch or develop the identified tool through coding or solution deep dives and scenario creation.
About the team
Rest of World (RoW) Supply CHain Analytics, Research and Product (SHARP) team supports supply chain processing for the multiple geographies like IN, Japan, Mexico, Brazil, MENA, AU & SG. The research team works to support network design, labor planning and capacity planning processes through launching decision support tools for planning or execution.
Basic Qualifications
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred Qualifications
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of MIP strategies to customize and leverage commercial algorithms and adapt them as required
- Experience working with or evaluating AI systems
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
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.
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Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
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Employees
Seattle
Headquarters
$1.5T
Valuation
Reviews
3.4
10 reviews
Work-life balance
2.5
Compensation
4.2
Culture
3.0
Career
3.8
Management
2.7
65%
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Pros
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
Cons
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
Salary Ranges
4 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 per year
Base
-
Stock
-
Bonus
-
$154,672
$209,264
Interview experience
6 interviews
Difficulty
4.0
/ 5
Duration
21-35 weeks
Experience
Positive 0%
Neutral 17%
Negative 83%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
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Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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