Engage with stakeholders across cross-functional projects and team settings to identify and clarify business or product questions to answer, while providing feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.

Leverage custom data infrastructure or existing data models as appropriate, using specialized knowledge to design and evaluate models that mathematically express and solve defined problems with limited precedent.

Work with the engineering and product teams to create new metrics, maintain classifiers, enable insights, and drive data-driven decision making.

Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python), formatting, re-structuring, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Support launch decisions through experimental design and analysis.

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

5 years of work experience using analytics to solve product or business
problems, coding (e.g., Python, R, SQL), querying databases or statistical
analysis, or 3 years of work experience with a PhD degree.

Experience with forecasting/time series.