Principal Data Scientist, Amazon

• A successful candidate will be customer obsessed - the Forecasting org has 50+ unique customers
• You will be comfortable navigating an ambiguous environment, presenting to senior and executive level audiences, know how to confirm and reconfirm assumptions, and be able to harmonize disparate points of view
• Bachelor's degree in data science or related field
• 10+ years of data scientist or related field
• 10+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment

Desirable

• We need your skills to optimize our supply chain, with the end goal of delighting our customers
• A core part of the supply chain operations is Demand and Inbound Forecasting: We forecast the demand and arrival of tens of millions of products
• The 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 WW warehouses
• We are looking for a Principal Data Scientist to take the lead on the design, implementation, and delivery of analytical and modeling solutions in a highly ambiguous and significantly complex environment
• You will do this by collaborating with senior leaders across organizations, detecting, diagnosing, and correcting problems and generating metrics and insights
• You will have the resources and tools to help you deliver this mission and support from partner teams like Data Engineering, Business Intelligence, Applied and Research Science, and Product
• You will need to balance long-term thinking with short-term actions
• Lead the design, implementation, and delivery of data science solutions for significantly complex problems that have a long-term impact on a product, business, or function
• Establish best practices and simplify problems
• Tackle intrinsically hard problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact)
• Deliver designs to algorithms to implementations to technical documents
• Provide data and measurements that influence the business strategy of an organization
• Lead and actively participate in reviews of data science solutions