Data Scientist - CloudTune , CloudTune Science
Seattle, Washington, USA
Full Time Mid-level / Intermediate USD 125K - 212K
Amazon.com
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Amazon’s eCommerce Foundation (eCF) organization provides the core technologies that drive and power Amazon's 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 Amazon’s 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 SDO-wide 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 region-flexible, 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, multi-year program which spans all Amazon business.
CloudTune is looking for a Data 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 a Data Scientist 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 be an expert at communicating insights and recommendations to audiences of varying levels of technical sophistication. You will lead the design, implementation, and delivery of data science solutions for complex capacity planning problems.
Key job responsibilities
- Research and develop new methodologies for capacity demand forecasting.
- Translate analytic insights into concrete, actionable recommendations for business or product improvement. Develop and present these as papers to senior stakeholders.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Drive scalable solutions for multi-year capacity demand forecasting horizons.
- Play an integral role in developing a roadmap to expand and enhance demand forecasting for cloud compute resources.
- Create and track accuracy and performance metrics (both technical and business metrics).
- Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
- Experience in a ML or data scientist role with a large technology company
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 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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 https://www.aboutamazon.com/workplace/employee-benefits. 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 SDO-wide 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 region-flexible, 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, multi-year program which spans all Amazon business.
CloudTune is looking for a Data 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 a Data Scientist 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 be an expert at communicating insights and recommendations to audiences of varying levels of technical sophistication. You will lead the design, implementation, and delivery of data science solutions for complex capacity planning problems.
Key job responsibilities
- Research and develop new methodologies for capacity demand forecasting.
- Translate analytic insights into concrete, actionable recommendations for business or product improvement. Develop and present these as papers to senior stakeholders.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Drive scalable solutions for multi-year capacity demand forecasting horizons.
- Play an integral role in developing a roadmap to expand and enhance demand forecasting for cloud compute resources.
- Create and track accuracy and performance metrics (both technical and business metrics).
- Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.
Basic Qualifications
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
Preferred Qualifications
- Experience in Python, Perl, or another scripting language- Experience in a ML or data scientist role with a large technology company
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 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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Category:
Data Science Jobs
Tags: AWS Data analysis E-commerce Engineering Machine Learning Matlab Perl Python R Research SAS SQL Statistical modeling Statistics
Perks/benefits: Career development Equity / stock options Startup environment Team events
Region:
North America
Country:
United States
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