Amazon has the world’s most complex supply chain: they fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. They need your skills to optimize their supply chain, with the end goal of delighting our customers. A core part of the supply chain operations is Demand Forecasting: Amazon forecast the demand of tens of millions of products. These forecasts are used to make many decisions, such as automatically order hundreds of millions worth of inventory, decide where to place that inventory, and establish labor plans for hundreds of warehouses.
The Demand Forecasting Team is looking for an analytical and technically skilled Data Scientist to join the team. This position will be responsible for developing and supporting best-in-class data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist needs to be familiar with deriving causal inferences using observational data and able to model variations related with demand prediction, out of stock, seasonality, and different lead times and spans. Upon completion of statistical analysis, the Data Scientist needs to communicate measurement results to stakeholders by translating technical framework to business-oriented insights.
This role requires an individual with excellent analytical abilities as well as outstanding business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had.
Key job responsibilities
- Collaborate with product managers and deep learning science and engineering teams to design and implement agile model solutions for Amazon demand core models
- Develop edge case agile models for on-going demand measurements toward the end goal of accurately predicting customer demand for millions of products world-wide
- Use large datasets or experiments to make causal inferences or predictions
- Work with engineers to automate science analysis processes and build scalable measurement solutions
- Interpret data, write reports, and make actionable recommendations
- Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and be able to clearly communicate appropriate triggers and actions
- Master’s degree (or Bachelor’s degree + 2 years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science
- 2+ years of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication
- 2+ years of experience using data querying languages (e.g. SQL), scripting languages e.g. Python, or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- 0-2 years of research experience working in statistical analysis
- Must have experience in Python, SQL, Stata, R and/or Scala.
- Experience modeling observational survey data
- Experience with modelling large individual-level datasets
- Experience of finding practical solutions for ambiguous and challenging business questions
- Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts
- Training in computer science, statistics, or highly quantitative field with 2+ years experience on a data, research, or applied science team
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1