A Logistic Regression developer designs, implements, and maintains statistical models, particularly logistic regression models, to predict and analyze categorical dependent variables. They collect, clean, and analyze data, then use programming languages such as Python or R to build models. They assess model performance using various metrics, optimize algorithms, and adjust model parameters to improve predictive accuracy. They also provide insights and recommendations based on model results to stakeholders. Additionally, they continually update models as new data becomes available and remain aware of the latest machine learning techniques and technologies.