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