Have you ever ordered a product on Amazon and when that box with the smile arrives you wonder how it got to you so fast? Wondered where it came from and how much it would have cost Amazon? If so, Amazon’s Supply Chain Optimization Technologies (SCOT) team is for you. We build systems to peer into the future and estimate the distribution of tens of millions of products every week to Amazon’s warehouses in the most cost-effective way. When customers place orders, our systems use real time, large scale optimization techniques to optimally choose where to ship from and how to consolidate multiple orders so that customers get their shipments on time or faster with the lowest possible transportation costs. This team is focused on saving hundreds of millions of dollars using cutting edge science, machine learning, and scalable distributed software on the Cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply.
Fulfillment-by-Amazon (FBA) Inventory Optimization (FIO) is a relatively new team at Amazon’s Supply Chain Optimization Technologies (SCOT). We focus on driving long term free cash flow by automating and optimizing our third-party supply chain. The team’s efforts will address the key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel. This is truly a unique problem space – optimizing for inventory in Amazon’s pipeline when you don’t control the process or own the inventory.
FIO is seeking an Research Scientist to join its cross-functional team of data, applied and research scientists, economists, engineers, and product managers to utilize cutting edge optimization models, econometrics, machine-learning, and distributed software on the Cloud to build systems that automate and optimize inventory management under the uncertainty of demand, pricing and supply. We are recruiting a curious and creative Research Scientist who will collaborate with other scientists and engineers to leverage new machine learning methods and algorithms for the modeling and analysis of data.
· PhD in a quantitative field such as Mathematics, Statistics, Machine Learning, Operational Research, Computer Science and 2+ years of industry experience OR MS in a quantitative field and 4+ years of experience
· Hands-on experience in building, iterating and validating statistical models, including regressions, clustering and other types of predictive modeling
· Proficiency working with R or Python
· Experience with SQL
· Strong communication and data presentation skills
· PhD in Computer Science, Statistics, Machine Learning, or a related quantitative field and 5+ years of hands-on experience applying theoretical models in an applied environment
· Extensive experience in causal inference, machine learning, statistical learning, and statistics
· Programming experience using at least one modern programming language such as Java or C++
· Proficiency in model development, model validation and model implementation for large-scale applications
· Experience with developing prototypes by manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
· Strong personal interest in learning, researching, and creating new technologies with high commercial impact