Worked on the pymc-labs/pymc-marketing repository to improve the reliability of data visualization for time-varying-intercept models. Focused on debugging and refining the plotting pipeline, the developer addressed a critical issue affecting the accurate display of the intercept’s mean over time. Using Python and leveraging skills in statistical modeling and data visualization, they implemented targeted fixes that ensured robust and accurate visual outputs for business analytics and marketing insights. The work included resolving a specific bug that previously caused incorrect plots, and introduced safeguards against future regressions, thereby enhancing the overall stability of the visualization workflow for these statistical models.