This role can sit in Seattle, WA, Nashville, TN, Arlington, VA (HQ2), other corporate locations would be considered.
The Amazon Forecasting and Science for Talents team is a key partner to talent strategy and planning teams across Amazon World-Wide (WW) Consumer, providing essential insights to optimize decision making processes across critical talent initiatives. We forecast out for tens of thousands of hires a year, and talent plan for many more, driving WW initiatives to discover and enable hiring the right people at the right time and place. Our Science team focuses specifically on the creation of predictive and prescriptive approaches by leveraging Machine Learning (ML) and Artificial Intelligence (AI).
Do you want to help build and coordinate one of the largest Global Workforce on the planet through the adoption of applied science at Amazon? Are you excited by using massive amounts of disparate data to develop AI/ML models? Are you thrilled to be a part of Amazon who has been pioneering and shaping the world’s AI/ML technology for decades? In this role you will closely partner with Amazon WW Ops, Finance, HR, and Talent Acquisition leadership teams, and with various engineering, data, and science teams across the company. Your goal will be to discover best in class approaches to help better understand and forecast talent movement and enable your customers to derive actionable plans from data.
We are looking for an Applied Scientist with expertise in time series forecasting who can work with senior leadership and also partner with highly technical experts to deliver applied science solutions. The Applied Scientist will be comfortable delivering applied science solutions and diving deep into implementing and testing efficient code to build and deploy predictive and prescriptive models on the AWS cloud. Finally, this person will be an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication.
· 4+ years of hands-on experience in predictive modeling and applied science · 1+ years of experience in an applied scientist, research scientist, data scientist or ML engineer role developing applied science solutions on the cloud · 1+ years of experience with dev/ops setting up both development and production infrastructures on the cloud · Advanced programming skills in Python and at least one other language, with impeccable code documentation for efficient knowledge sharing and reproducibility · Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment · Excellent communication skills with ability to explain complex technical concepts to non-technical audience while also efficiently interacting with deeply technical peers · Able to work in a diverse team
· Master’s degree or PhD in a highly quantitative field (Computer Sciences, Machine Learning, Statistics, Applied Mathematics, Operational Research, etc) · Experience practicing ML on the cloud and quickly cycling through ML initiatives at scale · Subject matter expertise in forecasting spatial and time dependent data · Ability to develop strategic, baselined, data modeling processes · Experience in People/HR/Talent or Supply Chain is a plus · Experience setting up ML infrastructure on the cloud is a plus · Publications or presentations in recognized ML journals or conferences is a plus
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