Data Scientist, PPE Product Intelligence

Amazon

Seattle, WA

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JOB DETAILS

SKILLS

Algorithms, Apache Hadoop, Apache Hive, Apache Spark, Big Data, Business Intelligence Software, Computer Programming, Cross-Functional, Customer Experience, Data Analysis, Data Clustering, Data Processing, Data Science, Data Sets, Experiment Design, Financial Modeling, Forecasting, IBM SPSS Statistical Package, International Sales, MATLAB, MapReduce, Math Software, Metrics, Performance Management, Performance Modeling, Pricing, Problem Solving Skills, Product Pricing, Python Programming/Scripting Language, Quantitative Analysis, R Programming Language, SQL (Structured Query Language), Sales, Scala Programming Language, Scientific Research, Scripting (Scripting Languages), Startup, Statistical Analysis System (SAS), Statistical Modeling, Statistics, Statistics Software, Supply Chain

LOCATION

Seattle, WA

POSTED

1 day ago

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-technical stakeholders at all levels A day in the life A day in the life No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else. You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration. Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders. You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field. Basic Qualifications - 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 Preferred Qualifications - 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) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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

About the Company

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

COMPANY SIZE

10,000 employees or more

INDUSTRY

Other/Not Classified

FOUNDED

1994

WEBSITE

http://Amazon.com/militaryroles

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