This role will sit in our new headquarters in Northern Virginia, where Amazon will invest $2.5 billion dollars, occupy 4 million square feet of energy efficient office space, and create at least 25,000 new full-time jobs.
The AWS Infrastructure Data Center Planning and Delivery (DCPD) Data Science team owns supply chain management activities at a global scale.
We consolidate usage and supply chain health data and forecasts at a variety of horizons to ensure that we have the right strategic lens associated with each decision we make.
We identify gaps to ensure that the AWS business is able to support any and all customers who want to capitalize on the scalability, flexibility, and cost-efficiency of AWS. Our actions and decisions decide the where, how, and what will make it into each of our data centers and we need you to help us to make those decisions and clearly explain the why.
The Business Insights and Optimization (BIO) team owns data science, engineering, and business intelligence solutions feeding this team.
We identify gaps in our capacity planning and delivery mechanisms and design/build systems which will fix those gaps.
We are end to end data product owners and the analysis, models we produce drives billions of dollars of decisions annually.
Data Scientists on this team have end to end range and capabilities.
They work directly with business owners to understand how they use data to drive their business.
They design modeling frameworks to dive deep into these raw sources of information to get the most out of the data they have.
They work directly with data engineers to build automated pipelines and production scale information systems and models.
They build automated tools which will allow their results to be shared with the business at scale.
They align with business owners to continuously track their work to ensure maximum impact from their projects.
They monitor performance of their work to evaluate whether improvements are needed after tracking has started in production.
· Advanced degree (M.S. or Ph.D.) in Engineering, Math, Statistics, Finance, Computer Science, or related industry experience.
· 3+ Years of experience in data science/analysis/engineering
· 2+ Years of experience applying Statistics/Data Science/Machine Learning
· 2+ Years of Scripting experience in Python/R or other scripting languages
· 2+ Years of SQL experience
· 2+ Years of experience in Data Visualization, using Tableau, R Shiny, other off the shelf products, or scripting directly
· Experience in modeling and optimization
· Working knowledge of AWS tech stack.
· Experience with clustered data processing (e.g. Hadoop, Spark, Map-reduce, Hive)
· Experience in communicating technically, at a level appropriate for the audience.
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