Bie, Ww Orc Classification

il y a 2 semaines

Luxembourg Amazon EU Sarl - A84 Temps plein

Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science, or related field.
- Experience in Business Intelligence, Data Analysis, or a similar role.
- Proficient in scripting languages (e.g., R, Python, SQL).
- Experience with one or more analytics visualization tools (e.g., Excel, Tableau, QuickSight, PowerBI).
- Strong understanding of A/B testing, sampling methodologies, and other statistical analysis.
- Proficient in descriptive statistics and familiar with inferential statistical methodologies.
- Exceptional communication skills, with the ability to convey complex ideas in a clear and concise manner.
- Strong critical thinking and problem-solving skills.

The Amazon ORC Classification Analytics 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.

Key job responsibilities

**Your responsibilities will include**:

- 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,

Luxembourg, LUX
- Knowledge of how to improve code quality and optimizes BI processes (e.g. speed, cost, reliability)
- Knowledge on modelling techniques

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