ADCI
Data Science, Science, consumer engagement
DataScientist,MAPLE-RecommenderSystem
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist, MAPLE - Recommender System at ADCI. Skills: Recommender systems, Machine learning, GenAI, Data science. Participate in model design. Develop models”
What You'll Achieve.
Help millions of customers; Advance Amazon's science
Industry & Context.
Solve hard science problems
What They're Looking For.
Must Have
3+ years data scientist experience, 3+ years SQL experience, 3+ years Python experience, 3+ years R experience, 3+ years machine learning experience, 3+ years statistical modeling experience, 1+ years AI systems experience, 1+ years creating educational content, Master's degree in STEM, Experience applying theoretical models, 2+ years causal machine learning
Nice to Have
PhD in STEM, Knowledge of ML concepts, Experience in Python, Experience in Perl, Experience in scripting language, Experience in ML role, Experience in data scientist role, Experience defining GenAI benchmarks, Experience working on multi-team projects, Experience applying quantitative analysis, Experience making data-driven decisions
What You'll Do.
Participate in model design
Improve recommendation models
Use uplift learning algorithms
Conduct statistical analysis
Work with distributed algorithms
Present science research
Publish science research
Mentor junior engineers
Mentor junior scientists
How You'll Work.
Team & Collaboration
Work with business teams; Work with engineering teams; Work with partner teams
Communication Scope
Present research; Publish research
Full Job Description
Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Develop and test new signals for improving recommendation models - Use supervised and uplift learning algorithms to improve customer experience - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers. Basic Qualifications: - 3+ 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 too
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