Data Scientist I, SHAKE
Actively Reviewing the ApplicationsAmazon
India
Full-Time
On-site
1–2 LPA
Posted 16 hours ago
•
Apply by June 16, 2026
Job Description
Description
Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist.
Key job responsibilities
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 108,300.00 - 160,000.00 USD annually
Company - Amazon.com Services LLC
Job ID: A3206663
Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist.
Key job responsibilities
- You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product.
- You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns.
- You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.
- You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders.
- You thrive in an agile and fast-paced environment on highly visible projects and initiatives.
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 108,300.00 - 160,000.00 USD annually
Company - Amazon.com Services LLC
Job ID: A3206663
Required Skills
Communication
Machine Learning
Engineering
Data Analysis
Agile
Python
SQL
Research
MATLAB
SAS
SPSS
Hadoop
Spark
Hive
Quantitative Analysis
Recommendation Systems
Business Intelligence
Internet
Mathematics
Gap analysis
Scripting languages
Scripting
Agile and
Evaluation
Data processing
Segmentation
Big Data
Generative
Business intelligence tools
Data sources
MACHINE
Statistical
Machine learning concepts
Algorithm
Reasoning
STEM
Research Papers
Generative AI
Gap
Multi-task
AI Tools
Querying
Cross-Functional Team
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