Data Scientist - Mathematical Statistics (Python, statsmodels/scipy)

Candidates must have strong Python skills and a solid foundation in mathematical statistics. Required knowledge includes hypothesis testing (t-test, chi-square, ANOVA), p-values and confidence intervals, correlation and regression analysis, and probability distributions. Proficiency with numpy, scipy, statsmodels, and pandas is essential, with the ability to interpret results and communicate assumptions and limitations clearly.

You will clean and wrangle datasets, select appropriate statistical tests, run analyses in scipy/statsmodels, and extract actionable insights. Typical tasks include designing/assessing experiments, computing effect sizes and power, fitting linear/logistic models, checking assumptions/diagnostics, constructing intervals, and summarizing findings for stakeholders with clear narratives and visual summaries. Work also includes maintaining reproducible notebooks and documenting methods.