Amazon.com Services LLC

Data Science, Science, north america stores

DataScientist,PPEProductIntelligence

$136–184k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Scientist, PPE Product Intelligence at Amazon.com Services LLC. Skills: Data Science, Machine Learning, Statistical Modeling, Experimentation. Design experiments. Run experiments”

What You'll Achieve.

Generate customer-relevant prices; Improve Seller Pricing; Optimize Customer experience; Surprise and delight customers; Achieve real-world impact; Improve generalization; Shift forecast quality; Drive supply chain impact; Drive financial impact

Industry & Context.

Data Science, Science, north america stores
Problems you'll solve

Solve business problems; Solve technology problems; Scientific approaches; Scientific thinking

What They're Looking For.

Must Have

3+ years data querying, 3+ years scripting languages, 3+ years statistical software, 2+ years data scientist experience, 3+ years ML/statistical modeling, 3+ years data analysis tools, 3+ years data analysis techniques

Nice to Have

Experience in Python, Experience in Perl, Experience in scripting language, Experience in ML role, Experience in data scientist role, Experience with large technology company

What You'll Do.

Evaluate foundation model performance

Improve foundation model performance

Lead evaluation model lifecycle

Experiment with models

Define success metrics

Obtain stakeholder sign-off

Measure real-world impact

Develop statistical models

Deploy statistical models

Perform exploratory data analysis

Identify opportunities

Inform model development

Translate research findings

Provide recommendations

How You'll Work.

Team & Collaboration

Cross-functional collaboration; Partner with leaders; Work with scientists; Work with engineers; Work with business teams

Communication Scope

Clear insights; Clear recommendations; Stakeholder review

Process & Methodology

Lifecycle management

Full Job Description

Amazon's Price Perception and Evaluation team is seeking a driven Data Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to build and scale an advanced self-learning scientific price estimation and product understanding system, regularly generating fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide. The Data Scientist will work closely with other research scientists, applied scientists, and SDEs to design and run experiments, conduct statistical analysis, research new algorithms, and find new ways to improve Seller Pricing to optimize the Customer experience. The Scientist will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. If you are a scientist who wants to work at the frontier of time series research, at a scale no academic lab or startup can match, and see your work deployed to real-world impact — this is the team for you. Key job responsibilities - Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals - Lead the end-to-end lifecycle of evaluation models — from research and experimentation through production launch — including defining success metrics, obtaining stakeholder sign-off, and managing rollout - Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes - Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools - Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development - Translate complex research findings into clear insights and recommendations for technical and non-technic

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