and SQL, with the ability to query databases and manipulate large datasets. Proficiency in key Python libraries for data science, including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, and Keras. Solid understanding of machine learning techniques, such as clustering, tree-based methods, boosting, text mining, and neural networks. Expertise More ❯
product-focused roles. Deep understanding of LTV modeling, forecasting, and experimental design. Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Advanced SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user More ❯
modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user More ❯
