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Are you passionate about solving unique problems facing customers at the scale of Amazon? Are you thrilled about utilizing statistical analysis, machine learning, data mining and leveraging vast amounts of Amazon data to decipher and infer customer shopping patterns? Do you revel in working with a diverse mix of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the perfect match!
Fashion is an incredibly fast-paced, visual, subjective realm that presents distinct problem domains such as product recommendations, product discovery, and assessment. The vision for Amazon Fashion is to transform Amazon into the number one online shopping spot for fashion customers by offering a large number of selections, inspiring and accurate recommendations, and an exceptional customer experience.
The mission of the Fit Science team within Fashion Tech is to innovate and create scalable machine learning (ML) solutions to deliver personalized fit and size recommendations to Amazon Fashion customers when they evaluate clothing or shoes online. The team seeks to hire a Data Scientist with a strong foundation in statistical analysis, machine learning, and data mining, a proven track record of effectively handling large, complex, and heterogeneous datasets, and who is driven to constantly grow as a Data Scientist.
Key job responsibilities
- You will be part of our Science team, working closely with applied scientists, data engineers, product managers, UX designers, and business partners to solve intricate problems through data analysis. Your analysis will directly enhance the performance of our ML-based recommendation systems, thereby improving the customer experience and influencing the roadmap for science and the product.
- You can effectively analyze complex and disparate datasets collected from various sources to gain significant insights.
- Excellent communication skills necessary to work with cross-functional team members, understand essential questions and gain the trust of senior leaders.
- You can successfully multitask between distinct tasks such as gap analysis of algorithm results, consolidating multiple disparate datasets, conducting business intelligence, analyzing engagement metrics, or presenting to stakeholders.
- You flourish in a fast-paced, agile environment working on highly visible projects and initiatives.
We are open to hiring candidates to work from any of our following locations:
Sunnyvale, CA, USA
- 3+ years of experience in data querying languages (e.g. ), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- 2+ years of data scientist experience
- 3+ years of experience in machine learning/statistical modelling, data analysis tools and techniques, as well as understanding the parameters that affect their performance
- Experience applying theoretical models in a practical environment
- Experience in an ML or data scientist role at a large technology company
Amazon is committed to fostering 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 statuses. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation takes into account the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600 per year in our lowest geographic market up to $212,800 per year in our highest geographic market. Pay is determined based on a variety of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the offered position, 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. Applicants should apply through our internal or external career site.
Fashion is an incredibly fast-paced, visual, subjective realm that presents distinct problem domains such as product recommendations, product discovery, and assessment. The vision for Amazon Fashion is to transform Amazon into the number one online shopping spot for fashion customers by offering a large number of selections, inspiring and accurate recommendations, and an exceptional customer experience.
The mission of the Fit Science team within Fashion Tech is to innovate and create scalable machine learning (ML) solutions to deliver personalized fit and size recommendations to Amazon Fashion customers when they evaluate clothing or shoes online. The team seeks to hire a Data Scientist with a strong foundation in statistical analysis, machine learning, and data mining, a proven track record of effectively handling large, complex, and heterogeneous datasets, and who is driven to constantly grow as a Data Scientist.
Key job responsibilities
- You will be part of our Science team, working closely with applied scientists, data engineers, product managers, UX designers, and business partners to solve intricate problems through data analysis. Your analysis will directly enhance the performance of our ML-based recommendation systems, thereby improving the customer experience and influencing the roadmap for science and the product.
- You can effectively analyze complex and disparate datasets collected from various sources to gain significant insights.
- Excellent communication skills necessary to work with cross-functional team members, understand essential questions and gain the trust of senior leaders.
- You can successfully multitask between distinct tasks such as gap analysis of algorithm results, consolidating multiple disparate datasets, conducting business intelligence, analyzing engagement metrics, or presenting to stakeholders.
- You flourish in a fast-paced, agile environment working on highly visible projects and initiatives.
We are open to hiring candidates to work from any of our following locations:
Sunnyvale, CA, USA
Basic Qualifications
- 3+ years of experience in data querying languages (e.g. ), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- 2+ years of data scientist experience
- 3+ years of experience in machine learning/statistical modelling, data analysis tools and techniques, as well as understanding the parameters that affect their performance
- Experience applying theoretical models in a practical environment
Preferred Qualifications
- Experience in Python, Perl, or another scripting language- Experience in an ML or data scientist role at a large technology company
Amazon is committed to fostering 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 statuses. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation takes into account the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600 per year in our lowest geographic market up to $212,800 per year in our highest geographic market. Pay is determined based on a variety of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the offered position, 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. Applicants should apply through our internal or external career site.
