Master's degree or PhD in Statistics, Biostatistics, Operations Research, Physics, Economics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience.
Relevant internship or work experience with data. Experience in quantitative methodologies with statistics and causal inference method.
Experience with statistical software (e.g., R, Python, S-Plus, SAS, or similar).
Preferred qualifications:
Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
Experience with machine learning on large datasets.
Ability to draw conclusions from data and recommend actions.
Ability to teach others and learn new techniques such as differential privacy.
Ability to select the right statistical tools given a data analysis problem.