DESCRIPTION Amazon's Automated Inventory Management (AIM) Planning Organization is looking for a Data Scientist to help invent the next generation of Amazon's Capacity and Constraint Management system - Automated Planning System (APS). APS will herald a a new era in Sales and Operations Planning (S&OP). APS emerges as a next-generation decision-making framework for Amazon's Worldwide (WW) fulfillment networks. In an industry first, APS seamlessly aligns Amazon's business controls by uniting cutting-edge supply and demand forecasts with a state-of-the-art coordination framework – respecting the distributed ownership of business logic and outcomes. As the centralized planning system, APS takes charge of coordinating all fulfillment, inventory, and operational decisions, maximizing WW Long Term Free Cash Flow (LTFCF) over a 1-year horizon
The AIM team is part of the Supply Chain Optimization Technology (SCOT) Team within the Operations Organization. The charter of the SCOT team is to maximize Amazon's return on our inventory investment in terms of Free Cash Flow and customer satisfaction. The planning organization within Amazon leads the S&OP, IPE and Capacity Planning functions.
As a Data Scientist on the this team, you will build a deep understanding of Amazon's supply chain systems, lead innovation in our forecasting capabilities and build principled solutions to identify improvement opportunities in our supply chain using the latest machine learning techniques. You will also work with a team of Product Managers, Business Intelligence Engineers and Software Engineers to research and build accurate predictive models and deploy automated software solutions to provide insights to business leaders at the most senior levels throughout the company. You will build models that make our data more actionable and help us make complex business decisions at scale.
To help describe some of our challenges, we created a short video about Supply Chain Optimization at Amazon -
Key job responsibilities
- Implement statistical and machine learning methods to solve complex business problems
- Research new ways to improve predictive and explanatory models
- Directly contribute to the design and development of automated prediction systems and ML infrastructure
- Build models that can detect supply chain defects and explain variance to the optimal state
- Collaborate with other researchers, software developers, and business leaders to define the scientific roadmap for this team
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA BASIC QUALIFICATIONS - Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
- 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Bachelor's degree
