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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- 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
- Implement of various sampling techniques with the ability to handle issues arising from sampling, like sampling biases.
- Complete statistical tests like hypothesis testing, including parametric and non-parametric tests and is familiar with A/B testing.A day in the life1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
- Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
- Experience applying theoretical models in an applied environment
- Experience working as a Data Scientist
- Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
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