Data Scientist, PPE Product Intelligence

Amazon • Seattle, WA

3d • $108,300 - $160,000 • Onsite

About The Position

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.

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
• Bachelor's degree

Nice To Haves

• Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
• Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

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-technical stakeholders at all levels

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: Mid Level