Applied Scientist CloudTune
Applied Scientist CloudTune
Posted on :
18-04-2025
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Job Description
Amazons eCommerce Foundation (eCF) organization provides the core technologies that drive and power Amazons Stores Digital and Other (SDO) businesses. Millions of customer page views and orders per day are enabled by the systems eCF builds from the ground up. CloudTune within eCF empowers growth and business agility needs by automatically and efficiently managing AWS capacity and business processes needed to safely meet Amazons customer demand. CloudTune serves its primary customers internal software teams through forecast driven automation of cost controllership capacity management and scaling. We predict expected load and drive procurement and allocation of AWS capacity for new product launches and high velocity events like Prime Day and Cyber Monday.
CloudTune in partnership with Region Flexibility is driving an SDOwide program to diversify our use of AWS regions beyond DUB IAD and PDX regions. The objective of the Diversify AWS Region Usage (DARU) program is to mitigate the risk of capacity concentration by encouraging teams to design workloads that are regionflexible utilize AWS automation such as Flexible Fleets to access multiple capacity pools and optimize workload placement so SDO efficiently utilizes AWS. This is a strategic highly visible multiyear program which spans all Amazon business.
CloudTune is looking for an Applied Scientist to join our forecasting team and support DARU program. The team develops sophisticated algorithms that involve learning from large amounts of past data such as actual sales website traffic merchandising activities promotions similar products and product attributes to forecast the demand for our compute infrastructure. These forecasts are used to determine the level of investment in capital expenditures promotional activity engineering efficiency projects and determining financial performance.
As an Applied Scientist in CloudTune you will work with other scientists software engineers data engineers and product managers on a variety of important applied machine learning problems in the area of time series modeling. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data develop new algorithms and improve existing approaches based on statistical models machine learning algorithms and big data solutions to automatically scale Amazons compute infrastructure optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.
Key job responsibilities
Process and analyze large data sets mining additional data sources as needed
Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures
Build statistical models and drive scalable solutions for multiyear capacity demand forecasting horizons
Prototype these models by using highlevel modeling languages such as R or Python
Create enhance and maintain technical documentation and present to other scientists and business leaders
3 years of building models for business application experience
PhD or Masters degree and 4 years of building machine learning models or developing algorithms for business application experience
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience programming in Java C Python or related language
3 years of handson predictive modeling and large data analysis experience
5 years of solving business problems through machine learning data mining and statistical algorithms experience
PhD in econometrics statistics industrial engineering operations research optimization data mining analytics or equivalent quantitative field
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
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.
CloudTune in partnership with Region Flexibility is driving an SDOwide program to diversify our use of AWS regions beyond DUB IAD and PDX regions. The objective of the Diversify AWS Region Usage (DARU) program is to mitigate the risk of capacity concentration by encouraging teams to design workloads that are regionflexible utilize AWS automation such as Flexible Fleets to access multiple capacity pools and optimize workload placement so SDO efficiently utilizes AWS. This is a strategic highly visible multiyear program which spans all Amazon business.
CloudTune is looking for an Applied Scientist to join our forecasting team and support DARU program. The team develops sophisticated algorithms that involve learning from large amounts of past data such as actual sales website traffic merchandising activities promotions similar products and product attributes to forecast the demand for our compute infrastructure. These forecasts are used to determine the level of investment in capital expenditures promotional activity engineering efficiency projects and determining financial performance.
As an Applied Scientist in CloudTune you will work with other scientists software engineers data engineers and product managers on a variety of important applied machine learning problems in the area of time series modeling. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data develop new algorithms and improve existing approaches based on statistical models machine learning algorithms and big data solutions to automatically scale Amazons compute infrastructure optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.
Key job responsibilities
Process and analyze large data sets mining additional data sources as needed
Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures
Build statistical models and drive scalable solutions for multiyear capacity demand forecasting horizons
Prototype these models by using highlevel modeling languages such as R or Python
Create enhance and maintain technical documentation and present to other scientists and business leaders
3 years of building models for business application experience
PhD or Masters degree and 4 years of building machine learning models or developing algorithms for business application experience
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience programming in Java C Python or related language
3 years of handson predictive modeling and large data analysis experience
5 years of solving business problems through machine learning data mining and statistical algorithms experience
PhD in econometrics statistics industrial engineering operations research optimization data mining analytics or equivalent quantitative field
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
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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