Amazon Worldwide Fulfillment Design and Engineering is looking to evolve the fulfillment center network of tomorrow by leveraging data and optimization tools to drive decision-making and solve complex, large-scale challenges.
Requirements
- 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
- Proficiency in data visualizations and dashboarding using AWS QuickSight Or Tableau and in MS Excel (including Pivots, VBA, etc.)
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Responsibilities
- Analyze, model and interpret data for Amazon warehouse operational performance
- Data analysis, modeling, network flow prediction using Excel, Pivot tables, VBA, Tableau, SQL (Amazon Redshift), R, Python
- Predictive analysis using Machine Learning models at scale
- Create effective data analysis reports and communicate with stakeholders
- Innovate and simplify data analysis process to standardize and enable automation
- Support Worldwide Engineering teams by providing necessary data for of process flows and selection of various MHE's
- Develop data and optimization-based solutions to the best-in-class process flow to improve the throughput of the fulfillment facilities.
Other
- Communicate design and technical requirements within the team and across stakeholder groups
- Learn current processes, build metrics, educate diverse stakeholder groups, assist science groups in initial solution design, and audit new flow implementations
- Communicating across significant differences, prioritizing competing requests, and quantifying decisions made
- Manage multiple data analysis projects and tasks simultaneously and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors
- Support process improvement initiatives among site operations, engineering, and corporate systems groups by providing relevant data.
