Senior Applied Scientist APSNOSO Science
Senior Applied Scientist APSNOSO Science
Posted on :
26-04-2025
Employer Active
1 Vacancy
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Yearly Salary
$ 150400 - 260000
Vacancy
1 Vacancy
Posted on :
26-04-2025
Job Description
Amazon Supply Chain forms the backbone of the fastest growing ecommerce business in the world. The sheer growth of the business and the companys mission to be Earths most customercentric company makes the customer fulfillment business bigger and more complex with each passing year.
The SC Science Optimization team is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our EU/NA fulfillment network.
The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain endtoend and deploying Operations Research Machine Learning Statistics and Econometrics models to improve decision making within our organization including forecasting planning and executing our network. We work closely with Supply Chain Optimization Technology (SCOT) teams who own the systems and the inputs we rely on to plan our networks the worldwide scientific community and with our internal EU stakeholders within Supply Chain Transportation Store and Finance.
We are looking for an experienced candidate having a wellroundedtechnical/science background with a particular expertise in stochastic optimization and probabilistic forecasting as well as a history of delivering complex scientific projects endtoend and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an everchanging operational environment.
As an Applied Scientist you will design develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic optimization. You will partner with other tech and science teams operations finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows.
This role requires a selfstarter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and . You are passionate resultsoriented and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs.
Key job responsibilities
Build stateofthe art robust and scalable Stochastic Optimization and Probabilistic Forecasting algorithms to drive optimal planning under uncertainty and in Amazon endtoend supply chain
Design and engineer algorithms using Cloudbased stateofthe art software development techniques
Think multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing ones
Prototype fast ensure early adoption via pilots integrate feedback into the models and iterate
Operationalize (i.e. deliver) your science solutions by closely partnering with internal customers understand their needs/blockers and influence their roadmap
Lead complex analysis and clearly communicate results and recommendations to leadership
Act as an active member of the science community by researching applying and publishing internally/externally the latest OR/ML techniques from both academia and industry
3 years of building machine learning models for business application experience
PhD or Masters degree and 6 years of applied research experience
Experience programming in Java C Python or related language
Experience with neural deep learning methods and machine learning
3 years of building models for business application experience
2 years experience with Stochastic Optimization techniques (e.g. Stochastic Linear Programming Stochastic Dynamic Programming) and ML for Probabilistic Forecasting
Sharp analytical abilities excellent written and verbal communication skills
Ability to handle ambiguity and fastpaced environment
Experience with modeling tools such as R scikitlearn Spark MLLib MxNet Tensorflow numpy scipy etc.
Experience with large scale distributed systems such as Hadoop Spark etc.
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in commercial OR tools (e.g. CPLEX Gurobi XPRESS)
Experience with AWS solutions such as EC2 DynamoDB S3 and Redshift
Reinforcement Learning
Timeseries Forecasting
Deep Learning
Familiarity with Operations concepts Planning Forecasting Optimization and Customer experience gained through work experience or graduate level education
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 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 $150400/year in our lowest geographic market up to $260000/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 SC Science Optimization team is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our EU/NA fulfillment network.
The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain endtoend and deploying Operations Research Machine Learning Statistics and Econometrics models to improve decision making within our organization including forecasting planning and executing our network. We work closely with Supply Chain Optimization Technology (SCOT) teams who own the systems and the inputs we rely on to plan our networks the worldwide scientific community and with our internal EU stakeholders within Supply Chain Transportation Store and Finance.
We are looking for an experienced candidate having a wellroundedtechnical/science background with a particular expertise in stochastic optimization and probabilistic forecasting as well as a history of delivering complex scientific projects endtoend and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an everchanging operational environment.
As an Applied Scientist you will design develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic optimization. You will partner with other tech and science teams operations finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows.
This role requires a selfstarter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and . You are passionate resultsoriented and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs.
Key job responsibilities
Build stateofthe art robust and scalable Stochastic Optimization and Probabilistic Forecasting algorithms to drive optimal planning under uncertainty and in Amazon endtoend supply chain
Design and engineer algorithms using Cloudbased stateofthe art software development techniques
Think multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing ones
Prototype fast ensure early adoption via pilots integrate feedback into the models and iterate
Operationalize (i.e. deliver) your science solutions by closely partnering with internal customers understand their needs/blockers and influence their roadmap
Lead complex analysis and clearly communicate results and recommendations to leadership
Act as an active member of the science community by researching applying and publishing internally/externally the latest OR/ML techniques from both academia and industry
3 years of building machine learning models for business application experience
PhD or Masters degree and 6 years of applied research experience
Experience programming in Java C Python or related language
Experience with neural deep learning methods and machine learning
3 years of building models for business application experience
2 years experience with Stochastic Optimization techniques (e.g. Stochastic Linear Programming Stochastic Dynamic Programming) and ML for Probabilistic Forecasting
Sharp analytical abilities excellent written and verbal communication skills
Ability to handle ambiguity and fastpaced environment
Experience with modeling tools such as R scikitlearn Spark MLLib MxNet Tensorflow numpy scipy etc.
Experience with large scale distributed systems such as Hadoop Spark etc.
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in commercial OR tools (e.g. CPLEX Gurobi XPRESS)
Experience with AWS solutions such as EC2 DynamoDB S3 and Redshift
Reinforcement Learning
Timeseries Forecasting
Deep Learning
Familiarity with Operations concepts Planning Forecasting Optimization and Customer experience gained through work experience or graduate level education
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 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 $150400/year in our lowest geographic market up to $260000/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.
Required Experience:
Senior IC
Employment Type
Full-Time
Key Skills
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