Business Intelligence Engineer I, Retail Business Service
Retail Business Services (RBS) supports Amazon’s Retail business growth WW through three core tasks: (a) Selection, where RBS sources, creates and enrich ASINs to drive GMS growth; (b) Defect Elimination, where RBS resolves inbound supply chain defects and develops root cause fixes to improve free cash flow; and (c) supports operational processes for WW Retail teams.
Our team of high-caliber software developers, applied scientists, data engineers, product managers, and Business Intelligence Engineers use rigorous ML and deep learning approaches to ensure that we identify and fix the right catalog defect to ensure a good shopping experience for our customers.
We are looking for a customer-obsessed Business Intelligence Engineer that thrives in a culture of data-driven decision-making who will be responsible for helping us hold a high bar for the RBS Data Engineering Team.
This individual will be responsible for driving/creating:
1. Experience working with large, multi-dimensional datasets from multiple sources.
2. Making recommendations for new metrics, techniques, and strategies to improve operational and quality metrics.
3. Proficient using at least one data visualization product (Tableau, Qlik, Amazon QuickSight, Power BI, etc.).
4. Experience in the deployment of Machine Learning and Statistical models.
5. Building new Python utilities and maintaining existing ones.
6. Enabling more efficient ad-hoc queries and analysis.
7. Working closely with research scientists, business analysts, and product leads to scale data.
8. Ensuring consistency between various platform, operational, and analytic data sources to enable faster and more efficient detection and resolution of issues.
9. Exploring and learning the latest AWS technologies to provide new capabilities and increase efficiencies.
10. Mentoring the team on analytics best practices.
BASIC QUALIFICATIONS
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc. experience.
- Experience with data visualization using Tableau, QuickSight, or similar tools.
- Experience with one or more industry analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g., t-test, Chi-squared).
- Experience with a scripting language (e.g., Python, Java, or R).
PREFERRED QUALIFICATIONS
- Master's degree or Advanced technical degree.
- Knowledge of data modeling and data pipeline design.
- Experience with statistical analysis, correlation analysis.
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