Amazon

Business Intelligence Engineer, Operational Risk & Compliance, AMET

Job Description

The Amazon ROC AMET team is looking for a creative problem solver, analytical and technically skilled Business Intelligence Engineer to join our dynamic team. This role requires an individual with excellent statistical and analytical abilities, deep knowledge of business intelligence solutions and data engineering practices as well as proficiency in hypothesis testing, including parametric and non-parametric tests and is familiar with A/B testing, understanding factors like random assignment, statistical power, p-values, confidence intervals, potential biases along with strong grasp of frequentist statistics. The ideal candidate will help us to build data pipelines and robust metrics decks, perform advanced statistical analysis, and measure the success of our model deployments. If you have a knack for translating complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences, we'd love to hear from you!

Key job responsibilities
Collaborate with cross-functional teams to understand business needs and provide data-driven recommendations. Ability to clearly articulate assumptions, methodologies, results, and implications. Able to present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding. Design and implement metrics to measure the success and effectiveness of classification models by understanding the nuances and potential pitfalls. Use visualization tools and develop data pipelines to publish the metrics to internal and external stake holders Implementation of various sampling techniques with the ability to handle issues arising from sampling, like sampling biases. Able to do statistical tests like hypothesis testing, including parametric and non-parametric tests and is familiar with A/B testing.- 10+ years of professional or military experience
- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining


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