Applied Scientist II Modeling and Optimization MOP
Applied Scientist II Modeling and Optimization MOP
Posted on :
15-03-2025
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1 Vacancy
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Job Description
Do you enjoy solving challenging problems and driving innovations in research Are you seeking for an environment with a group of motivated and talented scientists like yourself Do you want to create scalable optimization models and apply machine learning techniques to guide realworld decisions Do you want to play a key role in the future of Amazon transportation and operations North America Sort Centers (NASC) are experiencing growth and looking for a skilled highly motivated Research Scientist in partnership with the Modeling and Optimization (MOP) team.
The Sort Center network is the critical MiddleMile solution in the Amazon Transportation Services (ATS) group linking Fulfillment Centers to the Last Mile. The experience of our customers is dependent on our ability to efficiently execute volume flow through the middlemile network.
Key job responsibilities
An Applied Scientist
provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques.
collaborates effectively with Amazon internal business customers and is their trusted partner
is proactive and independent in discovering and resolving business painpoints within a given scope
is able to identify a suitable level of sophistication in resolving the different business needs
is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed
is aware of the limitations of their proposed solutions and is proactive in communicating them to the business and advances the application of sciences towards Amazon business problems by bringing new methods ideas and practices to the team and scientific community.
A day in the life
Your will be developing modelbased optimization simulation and/or predictive tools to identify and evaluate opportunities to improve customer experience network speed cost and efficiency of capital investment.
You will quantify the improvements resulting from the application of these tools and you will evaluate the tradeoffs between potentially competing objectives.
You will develop good communication skills and ability to speak at a level appropriate for the audience will collaborate effectively with fellow scientists software development engineers and product managers and will deliver business value in a close partnership with many stakeholders from operations finance IT and business leadership.
About the team
At the Modeling and Optimization (MOP) team we use mathematical optimization algorithm design statistics and machine learning to improve decisionmaking capabilities across WW Operations from first mile to last mile.
We focus on transportation topology labor and resource planning for fulfillment facilities routing science visualization research data science and development and process optimization.
We create models to simulate optimize and control the fulfillment network with the objective of reducing cost while improving speed and reliability.
We support multiple business lanes therefore maintain a comprehensive and objective view coordinating solutions across organizational lines where possible.
1 years of programming in Java C Python or related language experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience building machine learning models or developing algorithms for business application
Experience developing optimization models and algorithmic solutions tailored to particular business problems with stateoftheart optimizers (e.g. CPLEX Gurobi XPRESS)
Experience writing scripts to manipulate data and developing software in traditional programming languages (e.g. C/C Java Python SQL).
Excellent communication skills with both technical and nontechnical audiences.
Relevant work experience with demonstrated impact in decision support applications (e.g. scheduling vehicle routing facility location assignment problems revenue management)
Practical experience developing largescale decision support tools based on optimization technology and control theory
Familiarity with largescale simulation modeling
Familiarity with stochastic processes and optimization under uncertainty
Familiarity with forecasting and time series analysis
Familiarity with machine learning techniques and technologies
Familiarity with data visualization (e.g. R Tableau GIS software)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Sort Center network is the critical MiddleMile solution in the Amazon Transportation Services (ATS) group linking Fulfillment Centers to the Last Mile. The experience of our customers is dependent on our ability to efficiently execute volume flow through the middlemile network.
Key job responsibilities
An Applied Scientist
provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques.
collaborates effectively with Amazon internal business customers and is their trusted partner
is proactive and independent in discovering and resolving business painpoints within a given scope
is able to identify a suitable level of sophistication in resolving the different business needs
is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed
is aware of the limitations of their proposed solutions and is proactive in communicating them to the business and advances the application of sciences towards Amazon business problems by bringing new methods ideas and practices to the team and scientific community.
A day in the life
Your will be developing modelbased optimization simulation and/or predictive tools to identify and evaluate opportunities to improve customer experience network speed cost and efficiency of capital investment.
You will quantify the improvements resulting from the application of these tools and you will evaluate the tradeoffs between potentially competing objectives.
You will develop good communication skills and ability to speak at a level appropriate for the audience will collaborate effectively with fellow scientists software development engineers and product managers and will deliver business value in a close partnership with many stakeholders from operations finance IT and business leadership.
About the team
At the Modeling and Optimization (MOP) team we use mathematical optimization algorithm design statistics and machine learning to improve decisionmaking capabilities across WW Operations from first mile to last mile.
We focus on transportation topology labor and resource planning for fulfillment facilities routing science visualization research data science and development and process optimization.
We create models to simulate optimize and control the fulfillment network with the objective of reducing cost while improving speed and reliability.
We support multiple business lanes therefore maintain a comprehensive and objective view coordinating solutions across organizational lines where possible.
1 years of programming in Java C Python or related language experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience building machine learning models or developing algorithms for business application
Experience developing optimization models and algorithmic solutions tailored to particular business problems with stateoftheart optimizers (e.g. CPLEX Gurobi XPRESS)
Experience writing scripts to manipulate data and developing software in traditional programming languages (e.g. C/C Java Python SQL).
Excellent communication skills with both technical and nontechnical audiences.
Relevant work experience with demonstrated impact in decision support applications (e.g. scheduling vehicle routing facility location assignment problems revenue management)
Practical experience developing largescale decision support tools based on optimization technology and control theory
Familiarity with largescale simulation modeling
Familiarity with stochastic processes and optimization under uncertainty
Familiarity with forecasting and time series analysis
Familiarity with machine learning techniques and technologies
Familiarity with data visualization (e.g. R Tableau GIS software)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
Employment Type
Full-Time
Key Skills
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