Data Scientist I, SHAKE

Amazon • Seattle, WA

2d

About The Position

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.

Requirements

• 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)

Nice To Haves

• 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.

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.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level