Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Preferred qualifications:
Master's degree or PhD in Statistics, Computer Science, Engineering, or Mathematics.
5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, statistical analysis, or a PhD degree.
Experience in Deep Learning methods or Large Language Models.
Experience in working with human evaluation data such as surveys.
Experience in working with datasets in a distributed system.
Excellent communication, presentation, and problem-solving skills.
The team works with model and product teams to measure and improve data quality, collect and generate high quality data, develop evaluation methodologies, and enhance model performance.
Work with data sets, solve non-routine analysis problems, apply advanced methods as needed, conduct analysis that includes data gathering and requirements specification, processing, cleaning and curation, analysis, visualization, ongoing deliverables, and presentations.
Share analysis to stakeholders and organizations executives in order to share insights, influence product direction, and answer difficult questions regarding data quality measurement and impact on model performance.
Build and prototype analysis pipelines to provide insights at scale, and work with product teams to incorporate important analysis into existing framework and tools.
Interact cross-functionally with a wide variety of product and model teams, work with engineers to identify opportunities for design, and assess improvements of data quality and model performance.
