FBA organization is looking for a customer focused, analytically and technically skilled business intelligence engineer to support the Inventory Optimization organization's analytic needs.
This position will be part of the business analytics team responsible for building out analysis, visualization tools and processes for the FBA FIO businesses. The successful candidate will be able to retrieve, integrate, visualize and present critical data in a format that is immediately useful to improve the business decision process. This role requires an individual with excellent analytical abilities as well as deep business acumen and comfort with technical teams and systems. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and enjoying working with large scale of data.
Key job responsibilities
a. Collaborate with research sciences, product and technology teams in driving step function changes towards influencing seller experience improvements.
b. Collaborate with senior leadership to implement advanced analytics algorithms and model evaluation framework across Capacity and Inventory Management domains
b. Own analytics for key domains across inventory optimization services and deliver self-service analytics at scale
c. Own data governance and stewardship for business critical metrics that influence technology investment decisions
d. Analyze and visualize transaction data to determine seller behaviors, and output solid analysis with recommendations.
e. Create scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation.
f. Lead projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
g. Develop queries, statistical analysis, and visualizations for ad-hoc requests and projects, as well as ongoing reporting
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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